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Record W3183689488 · doi:10.1126/science.373.6552.265

Large survey finds questionable research practices are common

2021· article· en· W3183689488 on OpenAlexaff
Jop de Vrieze

Bibliographic record

VenueScience · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBig Data and Business Intelligence
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsSurvey researchData sciencePsychologyComputer scienceApplied psychology

Abstract

fetched live from OpenAlex

Dutch study finds 8% of scientists have committed fraud.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchResearch integrity
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptMetaresearchResearch integrity
Domain: Methods · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.065
metaresearch head score (Gemma)0.311
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.311
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.008
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.345
GPT teacher head0.456
Teacher spread0.110 · 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

Labeled directly by 2 models reading the full record.

Study designObservational
DomainMethods
GenreEmpirical · Commentary

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

Citations31
Published2021
Admission routes1
Has abstractyes

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