MétaCan
Menu
Back to cohort
Record W4253148760 · doi:10.1002/0470011815.b2a00001

Bias, Overview

2005· other· en· W4253148760 on OpenAlexaff
Bernard C. K. Choi, Anita W. P. Pak

Bibliographic record

VenueEncyclopedia of Biostatistics · 2005
Typeother
Languageen
FieldDecision Sciences
TopicReliability and Agreement in Measurement
Canadian institutionsUniversity of OttawaChronic Disease Prevention Alliance of Canada
Fundersnot available
KeywordsInterpretation (philosophy)Computer scienceStatisticsData scienceInformation retrievalMathematicsProgramming language

Abstract

fetched live from OpenAlex

Abstract This article provides an overview on bias. Bias is defined as the deviation of results or inferences from the truth, or processes leading to such deviation. The article also provides a catalogue of 109 biases at the following stages of research: literature review 4, study design 31, study execution 3, data collection 46, analysis 15, interpretation of results 7, and publication 3.

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)0.181
metaresearch head score (Gemma)0.507
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1810.507
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0190.012
Science and technology studies0.0020.005
Scholarly communication0.0120.011
Open science0.0030.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0310.004

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 head0.155
GPT teacher head0.385
Teacher spread0.230 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations4
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueEncyclopedia of BiostatisticsSame topicReliability and Agreement in MeasurementFrench-language works237,207