The most important discoveries of the past 50 years in gynaecological pathology
Bibliographic record
Abstract
The field of gynaecological pathology has grown from its infancy to a mature subspecialty over the last 50 years. What discoveries have led the way in this evolution? On the basis of personal experience and a survey of expert gynaecological pathologists, the following discoveries have been most impactful: (i) identification of the role of human papillomavirus in the aetiology of carcinoma of the lower genital tract; (ii) the emergence of international classification systems for gynaecological cancers (with cervical adenocarcinoma being the most recent example of this); (iii) the development of reliable immunohistochemistry as a diagnostic adjunct; (iv) discoveries around the aetiology and the relationship between serous carcinoma of the tube/ovary and the endometrium; and (v) identification of the role of oestrogen in the development of endometrial carcinoma and histological recognition of the precursor lesion atypical hyperplasia/endometrial intraepithelial neoplasia, and how recognition of the role of diethylstilboestrol in the aetiology of vaginal clear cell carcinoma led directly to this discovery. The history of each discovery and how it changed diagnostic pathology will be discussed in this review.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".