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Record W2156104288 · doi:10.4111/kju.2010.51.10.665

Active Surveillance for Favorable-Risk Prostate Cancer: A Short Review

2010· review· en· W2156104288 on OpenAlexaff
Nathan Lawrentschuk, Laurence Klotz

Bibliographic record

VenueKorean journal of urology · 2010
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsOverdiagnosisMedicineProstate cancerWatchful waitingProstateCancerProstatectomyGynecologyDiseaseProstate-specific antigenManagement of prostate cancerIntensive care medicineOncologyInternal medicine

Abstract

fetched live from OpenAlex

Active surveillance is becoming a more widely accepted management strategy in men with low-risk localized prostate cancer. This is in recognition of the knowledge that most men with such cancer are likely to die from other causes. The obvious benefits of active surveillance are reduced morbidity by delaying or avoiding radical gland therapy. These advantages should be balanced against appropriate selection criteria and triggers for moving to radical therapy while on active surveillance. The optimal method by which to identify the small number of men who will progress by use of clinical, biopsy, and imaging data is yet to be defined. Nevertheless, active surveillance is an appealing management option in selected men with prostate cancer and represents a solution to the significant problem of the overdiagnosis of clinically insignificant disease that accompanies prostate-specific antigen (PSA) screening.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.036
GPT teacher head0.363
Teacher spread0.327 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations13
Published2010
Admission routes1
Has abstractyes

Explore more

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