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Record W2045747371 · doi:10.1309/x76n1fjhad41urlf

Outcome for Repeated Biopsy of the Prostate

2007· article· en· W2045747371 on OpenAlexafffund
Fadi Brimo, Robin T. Vollmer, Jacques Corcos, Peter A. Humphrey, Tarek A. Bismar

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2007
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityJewish General HospitalMontreal General Hospital
FundersJewish General HospitalMcGill UniversityU.S. Department of Veterans Affairs
KeywordsBiopsyMedicineProstate cancerProstate-specific antigenAtypiaIntraepithelial neoplasiaProstateProstate biopsyCancerUrologyRadiologyInternal medicinePathology

Abstract

fetched live from OpenAlex

We studied the relationships between the outcome in the last follow-up prostate biopsy specimen and serum prostate-specific antigen (PSA), prostatic intraepithelial neoplasia (PIN), and atypical small acinar proliferations (ASAPs) at the occasion of the initial biopsy in 244 cases in which the initial specimen was negative for tumor and at least 1 follow-up biopsy was done. PSA levels and ASAPs were significantly associated with cancer in the follow-up biopsy specimen (<P < .005; logistic regression analysis); however, the presence of PIN in the initial biopsy specimen did not relate to cancer in the follow-up specimen (P > .1). Thus, the probability that a follow-up biopsy demonstrates cancer depends on PSA and ASAPs, and even when ASAPs are present, serum PSA exerts an influence. For example, low PSA values, 5 ng/mL (5 mug/L) or less, are associated with low probabilities of a positive follow-up biopsy result, even when ASAPs were present in the first biopsy specimen. For higher PSA values, the presence of ASAPs dramatically increases the probability of a positive follow-up biopsy result compared with cases with no atypia or PIN in the first biopsy specimen.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.452
Teacher spread0.382 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2007
Admission routes2
Has abstractyes

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