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Record W2904060958 · doi:10.1016/j.jid.2018.10.028

Research Techniques Made Simple: Network Meta-Analysis

2018· review· en· W2904060958 on OpenAlex
Jennifer Watt, Andrea C. Tricco, Sharon E. Straus, Areti Angeliki Veroniki, Gary Naglie, Aaron M. Drucker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Investigative Dermatology · 2018
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsWomen's College HospitalInstitute for Work & HealthPublic Health OntarioUniversity of TorontoBaycrest HospitalSt. Michael's Hospital
Fundersnot available
KeywordsInterpretabilityPairwise comparisonPsychological interventionMeta-analysisComputer scienceSystematic reviewSimple (philosophy)Reading (process)Risk analysis (engineering)PsychologyManagement scienceMedicineMEDLINEArtificial intelligenceEngineeringPolitical scienceNursing

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.

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
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablehigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.289
metaresearch head score (Gemma)0.087
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (broad), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2890.087
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0590.043
Bibliometrics0.0070.018
Science and technology studies0.0000.002
Scholarly communication0.0010.000
Open science0.0090.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0160.003

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 head0.937
GPT teacher head0.650
Teacher spread0.287 · 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