Proceedings of the 2017 National Toxicology Program Satellite Symposium
Bibliographic record
Abstract
The 2017 annual National Toxicology Program Satellite Symposium, entitled "Pathology Potpourri," was held in Montreal, Quebec, Canada at the Society of Toxicologic Pathology's 36th annual meeting. The goal of this symposium was to present and discuss challenging diagnostic pathology and/or nomenclature issues. This article presents summaries of the speakers' talks along with select images that were used by the audience for voting and discussion. Various lesions and other topics covered during the symposium included renal papillary degeneration in perinatally exposed animals, an atriocaval mesothelioma, an unusual presentation of an alveolar-bronchiolar carcinoma, a paraganglioma of the organ of Zuckerkandl (also called an extra-adrenal pheochromocytoma), the use of human muscle samples to illustrate the challenges of manual scoring of fluorescent staining, intertubular spermatocytic seminomas, medical device pathology assessment and discussion of the approval process, collagen-induced arthritis, incisor denticles, ameloblast degeneration and poorly mineralized enamel matrix, connective tissue paragangliomas, microcystin-LR toxicity, perivascular mast cells in the forebrain thalamus unrelated to treatment, and 2 cases that provided a review of the International Harmonization of Nomenclature and Diagnostic Criteria (INHAND) bone nomenclature and recommended application of the terminology in routine nonclinical toxicity studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.061 | 0.015 |
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".