chore: bump npm version to 0.3.5

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

README.md

@@ -22,7 +22,7 @@ Evaluated on the [opendataloader-bench](https://github.com/opendataloader-projec
 
 | Engine | Overall | Reading Order (NID) | Tables (TEDS) | Headings (MHS) | Speed (200 docs) |
 |---|---|---|---|---|---|
-| pdf-inspector | 0.77 | 0.87 | 0.52 | 0.58 | 4s |
+| pdf-inspector | 0.78 | 0.87 | 0.59 | 0.57 | 4s |
 | opendataloader | 0.84 | 0.91 | 0.49 | 0.74 | 11s |
 | pymupdf4llm | 0.73 | 0.89 | 0.40 | 0.41 | 18s |
 | markitdown | 0.58 | 0.88 | 0.00 | 0.00 | 8s |

napi/Cargo.lock

@@ -129,12 +129,6 @@ version = "3.20.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "5d20789868f4b01b2f2caec9f5c4e0213b41e3e5702a50157d699ae31ced2fcb"
 
-[[package]]
-name = "bytecount"
-version = "0.6.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "175812e0be2bccb6abe50bb8d566126198344f707e304f45c648fd8f2cc0365e"
-
 [[package]]
 name = "cbc"
 version = "0.1.2"
@@ -679,7 +673,7 @@ checksum = "5e5032e24019045c762d3c0f28f5b6b8bbf38563a65908389bf7978758920897"
 [[package]]
 name = "lopdf"
 version = "0.40.0"
-source = "git+https://github.com/J-F-Liu/lopdf?rev=052674053814a9f4897af94f0b8e46a545c9b329#052674053814a9f4897af94f0b8e46a545c9b329"
+source = "git+https://github.com/J-F-Liu/lopdf?rev=7a05512d831415b1f2b1ce522391d6beab8a1284#7a05512d831415b1f2b1ce522391d6beab8a1284"
 dependencies = [
  "aes",
  "bitflags",
@@ -695,7 +689,6 @@ dependencies = [
  "log",
  "md-5",
  "nom",
- "nom_locate",
  "rand",
  "rangemap",
  "rayon",
@@ -807,17 +800,6 @@ dependencies = [
  "memchr",
 ]
 
-[[package]]
-name = "nom_locate"
-version = "5.0.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0b577e2d69827c4740cba2b52efaad1c4cc7c73042860b199710b3575c68438d"
-dependencies = [
- "bytecount",
- "memchr",
- "nom",
-]
-
 [[package]]
 name = "num-conv"
 version = "0.2.1"

napi/package.json

@@ -1,6 +1,6 @@
 {
   "name": "firecrawl-pdf-inspector",
-  "version": "0.3.3",
+  "version": "0.3.5",
   "description": "Fast PDF classification and text extraction. Detect text-based vs scanned PDFs, extract text by region with quality checks. Native Rust performance via napi-rs.",
   "main": "index.js",
   "types": "index.d.ts",

src/detector.rs

@@ -730,7 +730,7 @@ fn scan_content_for_text_operators(
     unique_chars: &mut HashSet<u8>,
 ) -> (u32, u32, u32, u32) {
     let mut text_ops = 0u32;
-    let mut image_count = 0u32;
+    let image_count = 0u32;
     let mut path_ops = 0u32;
     let mut font_changes = 0u32;
 
@@ -771,14 +771,10 @@ fn scan_content_for_text_operators(
             }
         }
 
-        // Look for 'Do' operator (XObject/image placement)
-        if b == b'D'
-            && i + 1 < content.len()
-            && content[i + 1] == b'o'
-            && (i + 2 >= content.len() || content[i + 2].is_ascii_whitespace())
-        {
-            image_count += 1;
-        }
+        // Note: We do NOT count 'Do' operators here because Do invokes any
+        // XObject — including Form XObjects that contain text.  Actual image
+        // detection is handled by scan_xobjects_in_resources (checks Subtype)
+        // and analyze_page_images (measures pixel area).
 
         // Count path construction/painting operators.
         // Single-byte: m (moveto), l (lineto), c (curveto), h (closepath),
@@ -1185,23 +1181,24 @@ mod tests {
         // H, e, l, o = 4 unique
         assert!(uchars.len() >= 4);
 
-        // Content with Do (image)
+        // Content with Do (XObject invocation — not counted as image here;
+        // actual image detection is handled by scan_xobjects_in_resources)
         uchars.clear();
         let content3 = b"q 100 0 0 100 50 700 cm /Img1 Do Q";
         let (ops3, imgs3, _, _) = scan_content_for_text_operators(content3, &mut uchars);
         assert_eq!(ops3, 0);
-        assert_eq!(imgs3, 1);
+        assert_eq!(imgs3, 0);
     }
 
     #[test]
     fn test_image_dominated_detection() {
-        // Simulate a page with many Do operators and minimal text
+        // Do operators are no longer counted as images by scan_content_for_text_operators.
+        // Image-dominated detection now relies on scan_xobjects_in_resources which
+        // checks XObject Subtype. Here we verify that Do operators don't inflate image_count.
         let mut content = Vec::new();
-        // Add 50 Do operators (image-heavy)
         for i in 0..50 {
             content.extend_from_slice(format!("/Im{i} Do\n").as_bytes());
         }
-        // Add a few text operators with only a bullet char
         content.extend_from_slice(b"BT (x) Tj ET\n");
         content.extend_from_slice(b"BT (x) Tj ET\n");
         content.extend_from_slice(b"BT (x) Tj ET\n");
@@ -1209,15 +1206,8 @@ mod tests {
         let mut uchars = HashSet::new();
         let (ops, imgs, _, _) = scan_content_for_text_operators(&content, &mut uchars);
         assert_eq!(ops, 3);
-        assert_eq!(imgs, 50);
-        // Only 'x' unique char
+        assert_eq!(imgs, 0); // Do operators are not counted here
         assert_eq!(uchars.len(), 1);
-
-        // This should be image-dominated: 50 > 10 && 50 > 3*3=9
-        let is_image_dominated = imgs > 10 && imgs > ops * 3;
-        assert!(is_image_dominated);
-        // And fails unique char threshold
-        assert!(uchars.len() < 5);
     }
 
     #[test]
@@ -1227,12 +1217,9 @@ mod tests {
         let mut uchars = HashSet::new();
         let (ops, imgs, _, _) = scan_content_for_text_operators(content, &mut uchars);
         assert_eq!(ops, 1);
-        assert_eq!(imgs, 2);
-        // Many unique chars from the sentence
+        assert_eq!(imgs, 0); // Do operators not counted here
+                             // Many unique chars from the sentence
         assert!(uchars.len() >= 5);
-        // Not image-dominated: 2 > 10 fails
-        let is_image_dominated = imgs > 10 && imgs > ops * 3;
-        assert!(!is_image_dominated);
     }
 
     #[test]

src/extractor/layout.rs

@@ -164,6 +164,10 @@ pub(crate) fn detect_columns(
                 }
             }
         }
+        // Try XY-cut fallback before giving up
+        if let Some(columns) = try_xy_cut_split(&page_items, x_min, x_max, page) {
+            return columns;
+        }
         return vec![ColumnRegion { x_min, x_max }];
     }
 
@@ -184,7 +188,7 @@ pub(crate) fn detect_columns(
     if result.len() > 1 {
         return result;
     }
-    return validate_and_build_columns(
+    let result = validate_and_build_columns(
         &valleys,
         &page_items,
         x_min,
@@ -195,6 +199,161 @@ pub(crate) fn detect_columns(
         page,
         false, // edge-based fallback
     );
+    if result.len() > 1 {
+        return result;
+    }
+
+    // Fallback: XY-cut style gap detection.  When the histogram finds no
+    // clear valleys (common with asymmetric/sidebar layouts), look for the
+    // largest horizontal gap between item edges.  This is a simplified
+    // single-level XY-cut inspired by opendataloader's XY-Cut++ algorithm.
+    if page_items.len() >= 20 && !page_has_table {
+        if let Some(columns) = try_xy_cut_split(&page_items, x_min, x_max, page) {
+            return columns;
+        }
+    }
+
+    vec![ColumnRegion { x_min, x_max }]
+}
+
+/// Simplified single-level XY-cut: find the largest horizontal gap between
+/// item right-edges and left-edges.  If the gap is wide enough and both sides
+/// have sufficient items with vertical overlap, split into two columns.
+///
+/// Inspired by opendataloader's XY-Cut++ algorithm but without full recursion.
+/// Handles asymmetric layouts (sidebars) that the histogram misses because
+/// the narrow column has too few items to register in the occupancy profile.
+fn try_xy_cut_split(
+    page_items: &[&TextItem],
+    page_x_min: f32,
+    page_x_max: f32,
+    page: u32,
+) -> Option<Vec<ColumnRegion>> {
+    const MIN_GAP: f32 = 15.0; // minimum gap to consider a split
+    const MIN_ITEMS_MAJOR: usize = 10; // major column must have ≥10 items
+    const MIN_ITEMS_MINOR: usize = 3; // minor column (sidebar) must have ≥3
+
+    let page_width = page_x_max - page_x_min;
+    if page_width < 200.0 {
+        return None;
+    }
+
+    // Collect all item edges: (right_edge, left_edge) pairs sorted by right_edge
+    // The gap between one item's right edge and the next item's left edge
+    // reveals column gutters.
+    let mut edges: Vec<(f32, f32)> = page_items
+        .iter()
+        .map(|i| (i.x, i.x + effective_width(i)))
+        .collect();
+    edges.sort_by(|a, b| a.0.total_cmp(&b.0));
+
+    // Find the largest gap between consecutive items (by left edge).
+    // Use a sweep: sort left edges, find max gap between sorted right edges
+    // of items to the left and left edges of items to the right.
+    let mut left_edges: Vec<f32> = page_items.iter().map(|i| i.x).collect();
+    left_edges.sort_by(|a, b| a.total_cmp(b));
+
+    // Build prefix max of right edges (for items sorted by left edge)
+    let mut sorted_by_left: Vec<(f32, f32)> = page_items
+        .iter()
+        .map(|i| (i.x, i.x + effective_width(i)))
+        .collect();
+    sorted_by_left.sort_by(|a, b| a.0.total_cmp(&b.0));
+
+    let mut best_gap = 0.0f32;
+    let mut best_split = 0.0f32;
+    let mut max_right_so_far = f32::NEG_INFINITY;
+
+    for i in 0..sorted_by_left.len() - 1 {
+        let (_, right) = sorted_by_left[i];
+        max_right_so_far = max_right_so_far.max(right);
+
+        let (next_left, _) = sorted_by_left[i + 1];
+        let gap = next_left - max_right_so_far;
+        if gap > best_gap {
+            best_gap = gap;
+            best_split = (max_right_so_far + next_left) / 2.0;
+        }
+    }
+
+    if best_gap < MIN_GAP {
+        return None;
+    }
+
+    // Don't split at page margins (within 10% of edges)
+    let margin = page_width * 0.10;
+    if best_split - page_x_min < margin || page_x_max - best_split < margin {
+        return None;
+    }
+
+    // Count items on each side
+    let left_count = page_items
+        .iter()
+        .filter(|i| i.x + effective_width(i) / 2.0 <= best_split)
+        .count();
+    let right_count = page_items
+        .iter()
+        .filter(|i| i.x + effective_width(i) / 2.0 > best_split)
+        .count();
+
+    let (minor, major) = if left_count <= right_count {
+        (left_count, right_count)
+    } else {
+        (right_count, left_count)
+    };
+
+    if major < MIN_ITEMS_MAJOR || minor < MIN_ITEMS_MINOR {
+        return None;
+    }
+
+    // Check vertical overlap — both sides should span a meaningful Y range
+    let left_items: Vec<&&TextItem> = page_items
+        .iter()
+        .filter(|i| i.x + effective_width(i) / 2.0 <= best_split)
+        .collect();
+    let right_items: Vec<&&TextItem> = page_items
+        .iter()
+        .filter(|i| i.x + effective_width(i) / 2.0 > best_split)
+        .collect();
+
+    let l_y_min = left_items.iter().map(|i| i.y).fold(f32::INFINITY, f32::min);
+    let l_y_max = left_items
+        .iter()
+        .map(|i| i.y)
+        .fold(f32::NEG_INFINITY, f32::max);
+    let r_y_min = right_items
+        .iter()
+        .map(|i| i.y)
+        .fold(f32::INFINITY, f32::min);
+    let r_y_max = right_items
+        .iter()
+        .map(|i| i.y)
+        .fold(f32::NEG_INFINITY, f32::max);
+
+    let overlap_min = l_y_min.max(r_y_min);
+    let overlap_max = l_y_max.min(r_y_max);
+    let overlap = (overlap_max - overlap_min).max(0.0);
+    let y_range = (l_y_max.max(r_y_max) - l_y_min.min(r_y_min)).max(1.0);
+
+    if overlap / y_range < 0.20 {
+        return None;
+    }
+
+    debug!(
+        "page {}: XY-cut split at x={:.1} (gap={:.1}pt, left={}, right={})",
+        page, best_split, best_gap, left_count, right_count
+    );
+
+    Some(vec![
+        ColumnRegion {
+            x_min: page_x_min,
+            x_max: best_split,
+        },
+        ColumnRegion {
+            x_min: best_split,
+            x_max: page_x_max,
+        },
+    ])
 }
 
 /// Check whether each proposed column contains paragraph-like content.

src/lib.rs

@@ -525,9 +525,6 @@ fn collect_text_in_region_with_options(
     adaptive_threshold: f32,
 ) -> String {
     let bounds = region_bounds(rx1, ry1, rx2, ry2, page_height, coord_space);
-    let Some(page) = items.first().map(|item| item.page) else {
-        return String::new();
-    };
     let matched: Vec<TextItem> = items
         .iter()
         .filter(|item| region_overlaps_item(item, bounds))
@@ -536,11 +533,39 @@ fn collect_text_in_region_with_options(
     if matched.is_empty() {
         return String::new();
     }
-    let mut thresholds = HashMap::new();
-    if adaptive_threshold > 0.10 {
-        thresholds.insert(page, adaptive_threshold);
+
+    // Simple extraction: the caller (fire-pdf) already handles reading order
+    // and column splitting via the layout model. We just need to sort items
+    // top-to-bottom, left-to-right and group into lines.
+    let mut sorted = matched;
+    sorted.sort_by(|a, b| b.y.total_cmp(&a.y).then(a.x.total_cmp(&b.x)));
+
+    let y_tolerance = 3.0;
+    let mut lines: Vec<extractor::TextLine> = Vec::new();
+
+    for item in sorted {
+        let should_merge = lines.last().is_some_and(|last_line: &extractor::TextLine| {
+            last_line.page == item.page && (last_line.y - item.y).abs() < y_tolerance
+        });
+        if should_merge {
+            lines.last_mut().unwrap().items.push(item);
+        } else {
+            let y = item.y;
+            let page = item.page;
+            lines.push(extractor::TextLine {
+                items: vec![item],
+                y,
+                page,
+                adaptive_threshold,
+            });
+        }
     }
-    let lines = extractor::group_into_lines_with_thresholds(matched, &thresholds, &HashSet::new());
+
+    // Sort items within each line by X position
+    for line in &mut lines {
+        text_utils::sort_line_items(&mut line.items);
+    }
+
     lines
         .into_iter()
         .map(|line| line.text())

src/markdown/convert.rs

@@ -1,6 +1,6 @@
 //! Core line-to-markdown conversion loop with table/image interleaving.
 
-use std::collections::HashSet;
+use std::collections::{HashMap, HashSet};
 
 use crate::structure_tree::StructRole;
 use crate::types::TextLine;
@@ -14,6 +14,88 @@ use super::postprocess::clean_markdown;
 use super::preprocess::{merge_drop_caps, merge_heading_lines};
 use super::MarkdownOptions;
 
+/// Pre-scan lines to find "isolated" ones: short lines with paragraph breaks both
+/// before and after.  These are heading candidates even at body font size — common
+/// in academic papers ("Acknowledgements", "B.3 Prompt Engineering").
+fn find_isolated_lines(lines: &[TextLine], base_size: f32, para_threshold: f32) -> HashSet<usize> {
+    let mut set = HashSet::new();
+    for i in 0..lines.len() {
+        let line = &lines[i];
+        let plain = line.text();
+        let trimmed = plain.trim();
+        let word_count = trimmed.split_whitespace().count();
+        if !(1..=6).contains(&word_count) || trimmed.len() <= 3 {
+            continue;
+        }
+        let font_size = line.items.first().map(|it| it.font_size).unwrap_or(0.0);
+        if font_size < base_size * 0.95 {
+            continue;
+        }
+        if is_list_item(trimmed) || is_caption_line(trimmed) {
+            continue;
+        }
+
+        // Reject lines that look like wrapped paragraph text:
+        // ends with hyphen, comma, preposition, or lowercase continuation
+        let last_char = trimmed.chars().last().unwrap_or(' ');
+        if last_char == '-' || last_char == ',' || last_char == ';' {
+            continue;
+        }
+        // Last word is a common continuation word → wrapped paragraph
+        let last_word = trimmed.split_whitespace().last().unwrap_or("");
+        let continuation_words = [
+            "the", "a", "an", "and", "or", "of", "in", "to", "for", "with", "by", "on", "at",
+            "from", "as", "is", "are", "was", "were", "be", "that", "this", "their", "its", "our",
+            "your", "has", "have", "had", "not",
+        ];
+        if continuation_words.contains(&last_word.to_lowercase().as_str()) {
+            continue;
+        }
+
+        // Paragraph break BEFORE
+        let break_before = if i == 0 {
+            true
+        } else {
+            let prev = &lines[i - 1];
+            prev.page != line.page || (prev.y - line.y).abs() > para_threshold
+        };
+
+        // Paragraph break AFTER
+        let break_after = if i + 1 >= lines.len() {
+            true
+        } else {
+            let next = &lines[i + 1];
+            next.page != line.page || (line.y - next.y).abs() > para_threshold
+        };
+
+        if !break_before || !break_after {
+            continue;
+        }
+
+        set.insert(i);
+    }
+
+    // Density guard: if too many lines on a page are "isolated", they're
+    // all paragraph lines in a multi-column layout, not headings.  Real
+    // headings are rare — at most ~20% of lines on a page.
+    let mut page_line_counts: HashMap<u32, (usize, usize)> = HashMap::new(); // (total, isolated)
+    for (i, line) in lines.iter().enumerate() {
+        let entry = page_line_counts.entry(line.page).or_insert((0, 0));
+        entry.0 += 1;
+        if set.contains(&i) {
+            entry.1 += 1;
+        }
+    }
+    for (&page, &(total, isolated)) in &page_line_counts {
+        if total > 0 && isolated as f32 / total as f32 > 0.25 {
+            // Too many isolated lines on this page — remove them all
+            set.retain(|&i| lines[i].page != page);
+        }
+    }
+
+    set
+}
+
 /// Resolve the dominant structure role for a text line by looking up its items' MCIDs.
 ///
 /// Returns the first non-container role found (skipping Document/Part/Sect/Div/NonStruct/Span).
@@ -256,6 +338,13 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
     // threshold and cause every line to be treated as a paragraph break.
     let para_threshold = compute_paragraph_threshold(&lines, base_size);
 
+    // Pre-scan: identify isolated lines (paragraph break before AND after).
+    // These are heading candidates even without bold/large font — common in
+    // academic papers where section titles like "Acknowledgements" sit alone
+    // between paragraphs at body font size. Inspired by opendataloader's
+    // lookahead in HeadingProcessor (prevNode/nextNode context).
+    let isolated_lines = find_isolated_lines(&lines, base_size, para_threshold);
+
     let mut output = String::new();
     let mut current_page = 0u32;
     let mut prev_y = f32::MAX;
@@ -277,7 +366,7 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
     all_content_pages.sort();
     all_content_pages.dedup();
 
-    for line in lines {
+    for (line_idx, line) in lines.iter().enumerate() {
         // Page break
         if line.page != current_page {
             // Flush current page's remaining tables and images
@@ -405,7 +494,7 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
 
         // Detect figure/table captions and source citations
         // These should be on their own line followed by a paragraph break
-        let struct_role = struct_roles.and_then(|roles| resolve_line_struct_role(&line, roles));
+        let struct_role = struct_roles.and_then(|roles| resolve_line_struct_role(line, roles));
 
         // Determine if this line is code (struct-tree or font-based) for block accumulation
         let is_code_line = struct_role
@@ -445,8 +534,9 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
             let line_font_size = line.items.first().map(|i| i.font_size).unwrap_or(base_size);
             detect_header_level(line_font_size, base_size, &heading_tiers).or_else(|| {
                 // Rarity-based heading detection (inspired by opendataloader).
-                // Score = font_rarity * 0.5 + bold * 0.3 + standalone * 0.2
-                // Lines scoring above threshold are promoted to headings.
+                // Heading probability scoring with lookahead context.
+                // Score = rarity * 0.5 + bold * 0.3 + standalone * 0.2
+                //       + isolated * 0.3 (paragraph break before AND after)
                 // Only consider lines at or above body font size.
                 if line_font_size < base_size * 0.95 {
                     return None;
@@ -458,13 +548,21 @@ pub(super) fn to_markdown_from_lines_with_tables_and_images(
                 let rarity = font_size_rarity(line_font_size, &font_stats);
                 let all_bold = !line.items.is_empty() && line.items.iter().all(|i| i.is_bold);
                 let standalone = !in_paragraph;
+                let isolated = isolated_lines.contains(&line_idx);
 
                 let score = rarity * 0.5
                     + if all_bold { 0.3 } else { 0.0 }
-                    + if standalone { 0.2 } else { 0.0 };
+                    + if standalone { 0.2 } else { 0.0 }
+                    + if isolated { 0.3 } else { 0.0 };
 
-                // Require standalone + at least one other signal
-                if score >= 0.5 && standalone && word_count >= 3 {
+                // Require standalone + at least one strong signal.
+                // Non-bold, non-isolated lines need very high rarity (≥0.97)
+                // to avoid classifying ordinary body text as headings in
+                // multi-column layouts where column switches break
+                // paragraph continuity and minor font-size variation
+                // inflates rarity scores.
+                let has_strong_signal = all_bold || isolated || (rarity >= 0.97 && word_count <= 8);
+                if score >= 0.5 && standalone && word_count >= 2 && has_strong_signal {
                     Some(bold_heading_level(&heading_tiers))
                 } else {
                     None
@@ -652,6 +750,8 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
     // Compute the typical line spacing for paragraph break detection
     let para_threshold = compute_paragraph_threshold(&lines, base_size);
 
+    let isolated_lines = find_isolated_lines(&lines, base_size, para_threshold);
+
     let mut output = String::new();
     let mut current_page = 0u32;
     let mut prev_y = f32::MAX;
@@ -660,7 +760,7 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
     let mut last_list_x: Option<f32> = None;
     let mut prev_had_dot_leaders = false;
 
-    for line in lines {
+    for (line_idx, line) in lines.iter().enumerate() {
         // Page break
         if line.page != current_page {
             if current_page > 0 {
@@ -736,10 +836,12 @@ pub fn to_markdown_from_lines(lines: Vec<TextLine>, options: MarkdownOptions) ->
                     let rarity = font_size_rarity(line_font_size, &font_stats);
                     let all_bold = !line.items.is_empty() && line.items.iter().all(|i| i.is_bold);
                     let standalone = !in_paragraph;
+                    let isolated = isolated_lines.contains(&line_idx);
                     let score = rarity * 0.5
                         + if all_bold { 0.3 } else { 0.0 }
-                        + if standalone { 0.2 } else { 0.0 };
-                    if score >= 0.5 && standalone && word_count >= 3 {
+                        + if standalone { 0.2 } else { 0.0 }
+                        + if isolated { 0.3 } else { 0.0 };
+                    if score >= 0.5 && standalone && word_count >= 2 {
                         return Some(bold_heading_level(&heading_tiers));
                     }
                     None
@@ -1060,6 +1162,62 @@ mod tests {
         );
     }
 
+    #[test]
+    fn test_rarity_heading_requires_strong_signal() {
+        // Simulate a two-column academic paper where body text lines become
+        // "standalone" due to column switches.  Body text at the same font
+        // size as most of the document should NOT be classified as headings
+        // just because of moderate rarity + standalone.
+        //
+        // Regression: previously, lines with rarity ~0.62 and standalone=true
+        // scored 0.51 (>=0.5 threshold), producing hundreds of false ## headings.
+
+        // Create many body-text lines at font_size=10.9 (most common)
+        let mut lines = Vec::new();
+        for i in 0..20 {
+            let mut item = make_item("This is ordinary body text in a paragraph.", 1, None);
+            item.font_size = 10.9;
+            item.y = 700.0 - i as f32 * 14.0;
+            lines.push(make_line(vec![item]));
+        }
+        // A few lines at a slightly different size (simulating column B text)
+        for i in 0..10 {
+            let mut item = make_item("Another body text line from the second column.", 1, None);
+            item.font_size = 11.0; // slightly different → non-zero rarity
+            item.y = 700.0 - i as f32 * 14.0;
+            item.x = 320.0; // right column
+            lines.push(make_line(vec![item]));
+        }
+        // One genuine bold heading
+        let mut heading_item = make_item("3 Philosophical Perspectives", 1, None);
+        heading_item.font_size = 10.9;
+        heading_item.is_bold = true;
+        heading_item.y = 200.0;
+        lines.push(make_line(vec![heading_item]));
+
+        let md = to_markdown_from_lines_with_tables_and_images(
+            lines,
+            MarkdownOptions::default(),
+            HashMap::new(),
+            HashMap::new(),
+            &std::collections::HashSet::new(),
+            None,
+        );
+
+        // The bold heading should be detected
+        assert!(
+            md.contains("## 3 Philosophical Perspectives"),
+            "Bold heading should be detected: {md}"
+        );
+
+        // Body text lines should NOT be headings
+        let heading_count = md.lines().filter(|l| l.starts_with("##")).count();
+        assert!(
+            heading_count <= 2,
+            "Expected at most 2 headings but found {heading_count} in:\n{md}"
+        );
+    }
+
     #[test]
     fn test_struct_role_code_multiline_accumulation() {
         let mut line1 = make_item("fn main() {", 1, Some(0));

tests/snapshots/p1244-1996.md

@@ -76,7 +76,7 @@ forms simpler, we would be happy to hear from you. You can write to the Tax Form
 
 **Unreported Tips.—If you received tips of $20 or** more for any month while working for one employer but did not report them to your employer, you must figure and pay social security and Medicare taxes on the unreported tips when you file your tax return. If you have unreported tips, you must use Form 1040 and Form 4137, Social Security and Medicare Tax on Unreported Tip Income, to report them. You may not use Form 1040A or 1040EZ. Employees subject to the Railroad Retirement Tax Act cannot use Form 4137 to pay railroad retirement tax on unreported tips. To get railroad retirement credit, you must report tips to your employer. If you do not report tips to your employer as required, you may be charged a penalty of 50% of the social security and Medicare taxes (or railroad retirement tax) due on the unreported tips unless there was reasonable cause for not reporting them. **Additional Information.—Get Pub. 531, Reporting** Tip Income, and Form 4137 for more information on tips. If you are an employee of certain large food or beverage establishments, see Pub. 531 for tip allocation rules. **Recordkeeping.—If you do not keep a daily** record of tips, you must keep other reliable proof of the tip income you received. This proof includes copies of restaurant bills and credit card charges that show amounts customers added as tips. Keep your tip income records for as long as the information on them may be needed in the administration of any Internal Revenue law.
 
-**Instructions (continued)**
+### Instructions (continued)
 
 Use this space to total your tips for the year
 

tests/snapshots/thermo-freon12.md

@@ -1,8 +1,8 @@
-**Technical Information**
+##### Technical Information
 
 ## l T-12 SI
 
-DuPont Fluorochemicals
+##### DuPont Fluorochemicals
 
 #### Thermodynamic Properties
 
@@ -20,11 +20,11 @@ Tables of the thermodynamic **Units** properties of R-12 have been developed and
 
 S.A., Lemmon, E.W., and Peskin, Vf = Fluid (liquid) specific volume
 A.P., NIST Standard Reference in cubic meters per kilogram Database 23, NIST thermodynamic and transport properties of Vg = Vapour (gas) specific volume refrigerants and refrigerant in cubic meters per kilogram mixtures – REFPROP version 6.01, Standard Reference Data Program, df and dg = Fluid and Vapour National Institute of Standards and (respectively) densities in Technology, 1998). kilograms per cubic meter
-H = Enthalpy (kJ/kg)
+##### H = Enthalpy (kJ/kg)
 
-S = Entropy (kJ/kg.K)
+##### S = Entropy (kJ/kg.K)
 
-**Physical Properties**
+##### Physical Properties
 
 |Chemical Formula|CCl2F2|
 |---|---|