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Record W4283690014 · doi:10.1101/2022.06.27.22276964

Establishing a core set of open science practices in biomedicine: a modified Delphi study

2022· preprint· en· W4283690014 on OpenAlexaff
Kelly D. Cobey, Stefanie Haustein, Jamie Brehaut, Ulrich Dirnagl, Delwen Franzen, Lars G. Hemkens, Justin Presseau, Nico Riedel, Daniel Strech, Juan Pablo Alperín, Rodrigo Costas, Emily S. Sena, Thed N. van Leeuwen, Clare L. Ardern, Isabel O. L. Bacellar, Nancy Camack, Marcos Britto Corrêa, Roberto Buccione, Maximiliano Sérgio Cenci, Dean Fergusson, Cassandra Gould van Praag, Michael M. Hoffman, Renata Moraes Bielemann, Ugo Moschini, Mauro Paschetta, Valentina Pasquale, Valeria E. Rac, Dylan Roskams-Edris, Hermann Schätzl, Jo Anne Stratton, David Moher

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsMontreal Neurological Institute and HospitalDiabetes CanadaToronto General HospitalUniversity of TorontoOttawa HospitalUniversity Health NetworkUniversity of CalgaryPrincess Margaret Cancer CentreMcGill UniversityUniversity of OttawaDouglas CollegeSimon Fraser UniversityTed Rogers Centre for Heart ResearchUniversity of British ColumbiaVector Institute
FundersWellcome Trust
KeywordsDelphi methodOpen scienceVotingSet (abstract data type)Medical educationOperationalizationBest practiceInclusion (mineral)PsychologyPolitical scienceKnowledge managementComputer sciencePublic relationsMedicineSocial psychology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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
gemmaMetaresearchOpen science
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
gptMetaresearchOpen science
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement 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)0.173
metaresearch head score (Gemma)0.140
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.915

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1730.140
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0060.007
Scholarly communication0.0040.006
Open science0.0030.011
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.478
GPT teacher head0.580
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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

MetaresearchOpen science

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Other design
DomainMethods
GenreEmpirical

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

Citations3
Published2022
Admission routes1
Has abstractyes

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