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Record W2022566441 · doi:10.1097/pas.0000000000000254

Best Practices Recommendations in the Application of Immunohistochemistry in Urologic Pathology

2014· article· en· W2022566441 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

VenueThe American Journal of Surgical Pathology · 2014
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcMaster UniversityCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsMedicineAnatomical pathologyPathologyConsensus conferenceMEDLINESurgical pathologyBest practiceImmunohistochemistryInternal medicineBiology

Abstract

fetched live from OpenAlex

Members of the International Society of Urological Pathology (ISUP) participated in a half-day consensus conference to discuss guidelines and recommendations regarding best practice approaches to use of immunohistochemistry (IHC) in differential diagnostic situations in urologic pathology, including bladder, prostate, testis and, kidney lesions. Four working groups, selected by the ISUP leadership, identified several high-interest topics based on common or relevant challenging diagnostic situations and proposed best practice recommendations, which were discussed by the membership. The overall summary of the discussions and the consensus opinion forms the basis of a series of articles, one for each organ site. This Special Article summarizes the overall recommendations made by the four working groups. It is anticipated that this ISUP effort will be valuable to the entire practicing community in the appropriate use of IHC in diagnostic urologic pathology.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.033
GPT teacher head0.342
Teacher spread0.309 · 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