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Record W2042319973 · doi:10.1002/pst.443

On assessing the presence of evaluation‐time bias in progression‐free survival in randomized trials

2010· article· en· W2042319973 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePharmaceutical Statistics · 2010
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsRandomized controlled trialComputer scienceTest (biology)Log-rank testRandomized experimentProgression-free survivalStatisticsEconometricsOverall survivalSurvival analysisMedical physicsMedicineOncologyMathematicsInternal medicine

Abstract

fetched live from OpenAlex

Evaluation (or assessment)-time bias can arise in oncology trials that study progression-free survival (PFS) when randomized groups have different patterns of timing of assessments. Modelling or computer simulation is sometimes used to explore the extent of such bias; valid results require building such simulations under realistic assumptions concerning the timing of assessments. This paper considers a trial that used a logrank test where computer simulations were based on unrealistic assumptions that severely overestimated the extent of potential bias. The paper shows that seemingly small differences in assumptions can lead to dramatic differences in the apparent operating characteristics of logrank tests.

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.

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)0.131
metaresearch head score (Gemma)0.901
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.770
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1310.901
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.795
GPT teacher head0.693
Teacher spread0.102 · 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