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Record W2267103748 · doi:10.1177/160940691501400203

Special Issue: Mixed Methods

2015· article· en· W2267103748 on OpenAlexaff
Anthony J. Onwuegbuzie, Cheryl Poth

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2015
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLicenseWork (physics)ReproductionAttributionComputer scienceOperations researchMathematicsEngineeringPsychologyMechanical engineeringOperating systemSocial psychology

Abstract

fetched live from OpenAlex

© 2015 Onwuegbuzie & Poth. This is an Open Access article distributed under the terms of the Creative Commons‐ Attribution-NonCommercial-ShareAlike License 4.0 International (http://creativecommons.org/licenses/by-ncsa/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly attributed, not used for commercial purposes, and if transformed, the resulting work is redistributed under the same or similar license to this one.

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)0.058
metaresearch head score (Gemma)0.257
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.284
Threshold uncertainty score0.949

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.257
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0080.007
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0050.006
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.2840.078

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 head0.966
GPT teacher head0.872
Teacher spread0.093 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations15
Published2015
Admission routes1
Has abstractyes

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