MétaCan
Menu
Back to cohort

Classification of feline intraocular neoplasms based on morphology, histochemical staining, and immunohistochemical labeling

2006· article· en· W1993621828 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVeterinary Ophthalmology · 2006
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsUniversity of Prince Edward IslandUniversity of Saskatchewan
Fundersnot available
KeywordsPathologyImmunohistochemistryCiliary bodyBiologyStainingSarcomaStainSurgical pathologyMedicine

Abstract

fetched live from OpenAlex

The objectives of this study were to evaluate morphologic, histochemical, and immunohistochemical characteristics of well-differentiated and anaplastic intraocular neoplasms of cats, and to develop a diagnostic algorithm for, and investigate the association of ruptured lenses with these neoplasms. Seventy-five feline globes with intraocular neoplasms were stained with hematoxylin and eosin and examined by light microscopy. Morphologic diagnoses included 33 intraocular sarcomas, 17 diffuse iris melanomas, 15 lymphosarcomas, three ciliary adenomas, one metastatic carcinoma, and six undifferentiated intraocular neoplasms. Sections of these globes were then stained with periodic acid Schiff (PAS), and immunohistochemical (IHC) labels for various cellular markers. Histochemical staining and IHC labeling confirmed cellular differentiation in 73/75 neoplasms but was discordant with morphologic diagnoses in 8/75. These included four neoplasms morphologically diagnosed as lymphosarcomas but which expressed differentiation antigens consistent with melanoma (n = 3) or ciliary adenocarcinoma (n = 1), and four tumors morphologically diagnosed as intraocular sarcomas that expressed differentiation antigens for melanoma (n = 2), metastatic carcinoma (n = 1), or remained undifferentiated (n = 1). Immunohistochemical labeling suggested a diagnosis in 5/6 morphologically undifferentiated neoplasms including one intraocular sarcoma, two diffuse iridal melanomas, and two ciliary adenocarcinomas. Based upon morphologic, histochemical, and IHC characterization, ruptured lens capsules were detected in 28/30 intraocular sarcomas, 3/24 diffuse iris melanomas and 1/11 lymphosarcomas, but not in ciliary epithelial neoplasms, metastatic carcinomas, or undifferentiated intraocular neoplasms. An algorithm is provided that facilitates stain and IHC label selection for differentiating anaplastic intraocular feline neoplasms.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.357
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it