Update eval numbers to post-crop Hidden Trespass at validation-selected operating point

README.md

@@ -25,8 +25,10 @@ footers, footnotes).
 - **Paper:** [buda-base/papers](https://github.com/buda-base/papers) (`papers/2026-tibetan-book-layout`) — *arXiv link forthcoming*
 - **Code:** [github.com/buda-base/tibla](https://github.com/buda-base/tibla)
 
-> This checkpoint is **seed 0**; across five training seeds the paper reports
-> mean F1 **0.961 ± 0.009** (this seed scores 0.959, just below the mean).
+> This checkpoint is **seed 0**. Across five training seeds the paper reports
+> mean canonical F1 **0.961 ± 0.009** (unified scorer, per-seed operating point);
+> at the validation-selected operating point used in the table below this seed
+> scores **0.952**.
 
 ## Task
 
@@ -64,8 +66,8 @@ Footnote is deliberately kept low (recall-safe): the v4 test has only 38 footnot
 GT boxes, so a low threshold keeps recall near 1.0. Raising `header`/`footer` from
 0.25 to 0.60 lifts precision +0.028 for a −0.014 recall cost; raising `text-area`
 from 0.25 to 0.55 (native) lifts precision +0.007 at no recall cost. If you prefer
-one global knob, the single best-mean-F1 confidence is **0.74** (costs ≈0.008 mean
-F1 vs per-class tuning).
+one global knob, the single validation-selected best-mean-F1 confidence is **0.64**
+(costs ≈0.008 mean F1 vs per-class tuning).
 
 ## Evaluation (TiBLAD v4, 833-page test)
 
@@ -73,36 +75,40 @@ F1 vs per-class tuning).
 |---|---|---|---|
 | license | **AGPL-3.0** | Apache-2.0 | Apache-2.0 |
 | base model | **RT-DETR-l (Ultralytics)** | PP-DocLayout-L (PaddleOCR, RT-DETR-L) | RF-DETR-L (Roboflow) |
-| mean F1 (canonical 3-class) | **0.959** | 0.958 | 0.927 |
-|   header-footer F1 | **0.952** | 0.951 | 0.949 |
-|   text-area F1 | **0.999** | 0.997 | 0.996 |
-|   footnote F1 | **0.925** | 0.925 | 0.835 |
+| mean F1 (canonical 3-class) | **0.952** | 0.955 | 0.921 |
+|   header-footer F1 | **0.954** | 0.953 | 0.947 |
+|   text-area F1 | **0.999** | 0.998 | 0.996 |
+|   footnote F1 | **0.902** | 0.914 | 0.821 |
 | mean AP@0.50 | **0.974** | 0.959 | 0.925 |
 | mean AP@[0.50:0.95] | **0.786** | 0.781 | 0.667 |
 | shared-class mAP@[.50:.95] (DocLayNet-aligned) | **0.650** | 0.641 | 0.604 |
-| Hidden Trespass — header/footer | **0.008** | 0.003 | 0.020 |
-| Hidden Trespass — footnote | **0.037** | 0.037 | 0.216 |
+| Hidden Trespass — header/footer | **0.009** | 0.004 | 0.021 |
+| Hidden Trespass — footnote | **0.043** | 0.037 | 0.178 |
 | COTe (Trespass) | **0.975 (0.001)** | 0.978 (0.000) | 0.974 (0.002) |
-| operating confidence | **0.74** | 0.68 | 0.26 |
+| operating confidence | **0.64** | 0.61 | 0.47 |
 
-*"operating confidence" is the single global best-mean-F1 confidence used for the
-reported F1.*
+*"operating confidence" is the single global best-mean-F1 confidence, selected on
+the leak-free validation split and frozen for test (no test-set tuning). COCO AP
+rows are threshold-free (all detections above the fixed 0.05 floor).*
 
-**Hidden Trespass** = the missed peripheral (header/footer/footnote) ground-truth
-**area** that falls inside the predicted `text-area` crop; area-based,
-micro-averaged over the test set. Lower is better (less clutter bled into the OCR
-region). Formal definition in the [paper](https://github.com/buda-base/papers).
+**Hidden Trespass** = peripheral (header/footer/footnote) ground-truth **area**
+that survives in the *actual OCR body crop* `C = E \ P`, where `E` is the predicted
+`text-area` envelope and `P` is the union of the predicted peripheral boxes the
+pipeline subtracts; area-based, micro-averaged over the test set. Lower is better
+(less peripheral text bled into the OCR region). Formal definition in the
+[paper](https://github.com/buda-base/papers).
 
 ## Which checkpoint to pick
 
 | checkpoint | license | mean F1 | shared mAP | footnote HT |
 |---|---|---|---|---|
-| **TiBLA-RTDETR** (primary) | AGPL-3.0 | 0.959 | 0.650 | 0.037 |
-| TiBLA-PP-DocLayout-L | Apache-2.0 | 0.958 | 0.641 | 0.037 |
-| TiBLA-RFDETR | Apache-2.0 | 0.927 | 0.604 | 0.216 |
+| **TiBLA-RTDETR** (primary) | AGPL-3.0 | 0.952 | 0.650 | 0.043 |
+| TiBLA-PP-DocLayout-L | Apache-2.0 | 0.955 | 0.641 | 0.037 |
+| TiBLA-RFDETR | Apache-2.0 | 0.921 | 0.604 | 0.178 |
 
-RT-DETR-l has the top scores but its weights are AGPL-3.0 (Ultralytics). If you
-need a permissive license, PP-DocLayout-L matches it at Apache-2.0; RF-DETR is a
+RT-DETR-l leads on mAP, shared-class mAP and the 5-seed mean F1 (0.961 ± 0.009),
+but its weights are AGPL-3.0 (Ultralytics). If you need a permissive license,
+PP-DocLayout-L is an Apache-2.0 match (statistically on par on F1); RF-DETR is a
 lighter PyTorch-native Apache-2.0 option.
 
 ## Citation