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Record W2800256470 · doi:10.3747/co.25.3818

Male Oncology Research and Education Program for Men at High Risk for Prostate Cancer

2018· article· en· W2800256470 on OpenAlexaffvenue
Justin Lorentz, Stanley K. Liu, Danny Vesprini

Bibliographic record

VenueCurrent Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsProstate cancerMedicineProstate cancer screeningPopulationFamily medicineCancerOncologyProstate-specific antigenFamily historyObservational studyGynecologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Three groups of men are at high risk of developing prostate cancer: men with a strong family history of prostate cancer, men of West African or Caribbean ancestry, and men with a germline pathogenic variant in a prostate cancer-associated gene. Despite the fact that those men constitute a significant portion of the male population in North America, few recommendations for prostate cancer screening specific to them have been developed. For men at general population risk for prostate cancer, screening based on prostate-specific antigen (psa) has remained controversial despite the abundance of literature on the topic. As a result, recommendations made by major screening authorities are inconsistent (ranging from no psa screening to baseline psa screening at age 45), allowing physicians to pick and choose how to screen their patients. The Male Oncology Research and Education (more) program is an observational research program that serves as an academic platform for multiple research foci. For its participants, serum and dna are biobanked, medical information is collected, and contact for relevant research-related opportunities is maintained. This research program is paired with a specialized clinic called the more clinic, where men at high risk are regularly screened for prostate cancer in a standard approach that includes physical examination and serum psa measurement. In this article, we describe the goals, participant accrual to date, and projects specific to this unique program.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0430.007

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 head0.179
GPT teacher head0.536
Teacher spread0.357 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2018
Admission routes2
Has abstractyes

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