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Record W2014232120 · doi:10.3747/co.v17i0.713

Active Surveillance for Prostate Cancer: Patient Selection and Management

2010· article· en· W2014232120 on OpenAlexaffvenue
Laurence Klotz

Bibliographic record

VenueCurrent Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineProstate cancerDiseaseCancerProstateQuality of life (healthcare)Management of prostate cancerIntensive care medicineProstate-specific antigenOncologyInternal medicineGynecology

Abstract

fetched live from OpenAlex

Screening for prostate cancer using prostate-specific antigen (PSA) has been appealing. However, the significant associated decline in prostate cancer mortality comes at the cost of a very high rate of diagnosis, and many patients with indolent, non-life-threatening cancer are exposed to the risk of significant side effects from radical treatment. Most men with favourable-risk prostate cancer are not destined to die of their disease, even in the absence of treatment. The challenge is to identify the subset that harbour more aggressive disease early enough that curative therapy is still a possibility, thereby allowing the others to enjoy improved quality of life, free from the side effects of treatment. This article reviews current research into active surveillance in favourable-risk disease and some of the issues that arise when prostate cancer is monitored rather than being treated immediately.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.038
GPT teacher head0.381
Teacher spread0.343 · 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 designOther design
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

Citations61
Published2010
Admission routes2
Has abstractyes

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