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Record W4401846646 · doi:10.1016/j.jgo.2024.102047

Falls in older adults during treatment for metastatic castration-resistant prostate cancer

2024· article· en· W4401846646 on OpenAlexafffund
Saul Cobbing, Narhari Timilshina, George Tomlinson, Helen Yang, Valerie S. Kim, Urban Emmenegger, Shabbir M.H. Alibhai

Bibliographic record

VenueJournal of Geriatric Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsUniversity Health Network
FundersHunter Family Foundation
KeywordsMedicineProstate cancerOncologyInternal medicineCastrationGerontologyCancerHormone

Abstract

fetched live from OpenAlex

Despite major improvements in the management of prostate cancer over the past few decades, it remains a leading cause of death in Canadian men [1]. Almost all people who die from prostate cancer first develop metastatic castration-resistant prostate cancer (mCRPC). Although the majority of men with mCRPC are older adults - often 10 to 15 years older by the time of mCRPC diagnosis than at initial prostate cancer diagnosis - trials have recruited relatively young and fit men (with only one-quarter aged 75+) and focused on survival outcomes, quality of life (QOL), or symptom outcomes (including fatigue and pain) [2].

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.358
Teacher spread0.337 · 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

Citations2
Published2024
Admission routes2
Has abstractno

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