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Record W2493963530 · doi:10.1007/b138793

Advances in Ranking and Selection, Multiple Comparisons, and Reliability

2005· book· en· W2493963530 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

VenueBirkhäuser Boston eBooks · 2005
Typebook
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRanking (information retrieval)Selection (genetic algorithm)Reliability (semiconductor)Computer scienceStatisticsReliability engineeringMachine learningMathematicsEngineering

Abstract

fetched live from OpenAlex

13.1 Introduction and General Overview 215 13.2 Early Approaches 218 13.2.1 The limits of agreement (LOA) approach 219 13.2.2 Intraclass correlation and related measures 222 13.2.3 Concordance correlation approach 224 13.3 Recent Developments 226 13.3.1 Approaches based on percentiles and coverage probability 226 13.3.2 Approaches based on the intersection-union principle 229 13.4 An Example 232 13.5 Selection Problems in Measuring Agreement 235 13.5.1 Selection of the best 236 13.5.2 Assessment of agreement and selection of the best 238 13.

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)0.005
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.081
GPT teacher head0.382
Teacher spread0.301 · 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