Variable fidelity of tissue‐marking dyes in surgical pathology
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Pathology specimens often contain important margins that must be identified from gross examination of specimens through to microscopic examination. Commonly, unique colours of tissue-marking dye (TMD) are applied to each margin, which facilitates both macroscopic and microscopic identification. Various techniques have been described, but the colour endurance and fidelity of TMDs following special tissue processing have not been addressed. The aim of this study was to evaluate the performance of various TMDs through decalcification and immunohistochemistry (IHC) protocols. METHODS AND RESULTS: Samples of TMDs from two manufacturers and acrylic artists' inks were obtained in seven colours and applied to excess non-diagnostic surgical pathology tissue. Tissues were subjected to a decalcification protocol or directly processed in a routine fashion. The presence and colour of TMD or ink were assessed on routine H&E sections and following IHC. Of the colours that reliably survived routine processing, loss of colour and colour change following decalcification and IHC protocols were seen with one manufacturer's product. CONCLUSIONS: TMD may lose or change its colour during special tissue processing. This previously unreported artefact may lead to potentially serious errors in margin assessment and reporting. Laboratories should evaluate TMDs and inks through routine processing, decalcification, and IHC protocols, to ensure colour endurance and fidelity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it