Bibliographic record
Abstract
Edited by Mahul B Amin, Jesse K McKenney, Satish K Tickoo, Gladell P Paner, Steven S Shen, Elsa F Velazquez, Antonio L Cubilla, Jae Y Ro, Victor E Reut. Published by Amirsys Publishing, Altona, 2010, pp 1000, hardback, $299. ISBN-13 978-1-931884-28-0 Diagnostic Pathology: Genitourinary is the second book in Amirsys's new Diagnostic Pathology series after Diagnostic Pathology: Gastrointestinal . The books follow the same new concept, characterised by a large number of high-quality pictures, and succinct bulleted texts of short sentences, highlighting the epidemiology, clinical implications, gross and microscopic features, ancillary pathology techniques, including the growing field of molecular genetics, differential diagnosis and major clinical findings. The book further provides outlines of the handling of gross specimens with recommendations on how to achieve optimal results for staging purpose as well as checklists for reporting on the various specimens. I would like to congratulate the authors, all authorities in their field, with the results of their efforts, which have produced a book that competes well with other recent books of reference in the same field. Not only does it take a good concept to write an excellent book like this; it also takes the involvement of dedicated …
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.108 | 0.077 |
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".