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Record W1964059003 · doi:10.1080/07474940802619071

Discussion on “A Hybrid Selection and Testing Procedure with Curtailment for Comparative Clinical Trials” by Elena M. Buzaianu and Pinyuen Chen

2009· article· en· W1964059003 on OpenAlexafffundabout
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Bibliographic record

VenueSequential Analysis · 2009
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChenSelection (genetic algorithm)MathematicsParametric statisticsSequential analysisStatisticsBernoulli's principleStatistical hypothesis testingComputer scienceEconometricsArtificial intelligenceBiologyEngineering

Abstract

fetched live from OpenAlex

Testing for the equality of two Bernoulli populations in a fully sequential manner has been one of the examples in Gombay and Hussein (2006 Gombay , E. and Hussein , A. A. ( 2006 ). Sequential Comparison of Two Populations by Parametric Tests , Canadian Journal of Statistics 34 : 217 – 232 .[Crossref], [Web of Science ®] , [Google Scholar]). That procedure is explained with a possible application for the second stage of instead of the currently proposed one-step testing.

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)0.224
metaresearch head score (Gemma)0.273
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score0.957

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2240.273
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0020.002
Science and technology studies0.0020.015
Scholarly communication0.0040.008
Open science0.0080.004
Research integrity0.0130.012
Insufficient payload (model declined to judge)0.0060.001

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 head0.677
GPT teacher head0.617
Teacher spread0.060 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreCommentary

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

Citations0
Published2009
Admission routes3
Has abstractyes

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