MétaCan
Menu
Back to cohort
Record W4224922604 · doi:10.1111/cea.14144

Individual‐patient data and aggregate evidence syntheses and the future of allergy‐immunology research

2022· letter· en· W4224922604 on OpenAlexaff
Derek K. Chu

Bibliographic record

VenueClinical & Experimental Allergy · 2022
Typeletter
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare HamiltonImpact
Fundersnot available
KeywordsPsychological interventionAtopic dermatitisMeta-analysisAggregate dataSystematic reviewMedicineAggregate (composite)Raw dataMEDLINEPsychologyComputer scienceDermatologyPathologyPsychiatry

Abstract

fetched live from OpenAlex

Ability to respond to urgent or emergent health issues?Yes May be more difficult to coordinate and therefore, be successful Can explore impact of non-adherence?Yes Yes (more sophisticated approaches, e.g.complier average causal effect)Can explore subgroup or drug class effects?Yes Yes (more precise)

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)0.392
metaresearch head score (Gemma)0.601
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score0.749

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3920.601
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0100.009
Bibliometrics0.0250.020
Science and technology studies0.0030.014
Scholarly communication0.0340.040
Open science0.0070.014
Research integrity0.0140.019
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 head0.837
GPT teacher head0.598
Teacher spread0.238 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueClinical & Experimental AllergySame topicMeta-analysis and systematic reviewsFrench-language works237,207