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Record W2739029225 · doi:10.17615/qfnm-rd76

Redefine statistical significance

2025· article· en· W2739029225 on OpenAlexfundno aff
Judith Rousseau, Arthur Lupia, Edward I. George, Björn Brembs, Thomas D. Cook, Donald P. Green, Lawrence Brown, John P. A. Ioannidis, Yu Xie, Brian A. Nosek, Daniel J. Hruschka, Duncan J. Watts, Anthony G. Greenwald, Brendan Nyhan, Zoltán Dienes, Magnus Johannesson, Roderick J. A. Little, Felix D. Schönbrodt, Stephen L. Morgan, Timothy Parker, Leonhard Held, Larry V. Hedges, Steven N. Goodman, Andy P. Field, Colin F. Camerer, Kenny Easwaran, Kenneth A. Bollen, John A. List, Merlise A. Clyde, Guido W. Imbens, James H. Jones, Richard A. Berk, Jeff Rouder, Marcus R. Munafò, Charles Efferson, Simine Vazire, Daniel J. Benjamin, Chris Chambers, Paul De Boeck, James O. Berger, Robert L. Wolpert, Betsy Sinclair, Jarrod D. Hadfield, Thomas Sellke, Michael Kirchler, Ernst Fehr, Herbert Hoijtink, Richard Gonzalez, Luis R. Pericchi, Teck‐Hua Ho, Trisha Van Zandt, Edwin Green, Marco Perugini, Victoria Savalei, Anna Dreber, Eric‐Jan Wagenmakers, David Laibson, Kosuke Imai, Malcolm E. Forster, Shinichi Nakagawa, David Cesarini, Jonathan Zinman, Minjeong Jeon, Christopher Winship, Cristobal Young, Don A. Moore, Scott E. Maxwell, Dustin Tingley, Fiona Fidler, Édouard Machery, Valen E. Johnson

Bibliographic record

VenueArtefactual Field Experiments · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Computing and Data Management
Canadian institutionsnot available
FundersRoyal Holloway, University of LondonWeinberg College of Arts and Sciences, Northwestern UniversityUniversity of California, IrvineUniversity of California, Los AngelesUniversität InnsbruckUniversität ZürichUniversität RegensburgUniversiteit UtrechtWharton School, University of PennsylvaniaUniversiteit van AmsterdamUniversity of New South WalesGöteborgs UniversitetOhio State UniversityNational University of SingaporeUniversity of BristolColumbia UniversityUniversity of EdinburghMedical Research CouncilUniversity of SussexNorthwestern UniversityYork UniversityDartmouth CollegeCardiff UniversityUniversity of Notre DameUniversity of PittsburghPrinceton UniversityUniversity of WashingtonJohns Hopkins UniversityDirectorate for Biological SciencesImperial College LondonArizona State UniversityHarvard UniversityUniversità degli Studi di MilanoUniversity of PennsylvaniaUniversity of Southern CaliforniaSchool of Human Evolution and Social Change, Arizona State UniversityCalifornia Institute of Technology
KeywordsStatistical significanceValue (mathematics)StatisticsMathematics

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.164
metaresearch head score (Gemma)0.466
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: Commentary · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.870

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1640.466
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.004
Science and technology studies0.0030.009
Scholarly communication0.0060.007
Open science0.0050.006
Research integrity0.0040.017
Insufficient payload (model declined to judge)0.0120.002

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 head0.114
GPT teacher head0.445
Teacher spread0.331 · 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
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

Citations21
Published2025
Admission routes1
Has abstractno

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