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AHRQ series on complex intervention systematic reviews—paper 1: an introduction to a series of articles that provide guidance and tools for reviews of complex interventions

2017· review· en· W2734751589 on OpenAlex

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 Clinical Epidemiology · 2017
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsBruyèreUniversity of Ottawa
FundersAgency for Healthcare Research and QualityU.S. Department of Health and Human Services
KeywordsPsychological interventionIntervention (counseling)Systematic reviewMental healthMedicineHealth careMEDLINEPsychologyNursingPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Issues of complexity are taking primacy as research increasingly reflects the complexity of the world around us. Although advances in science have resulted in dramatic improvements in health and longevity worldwide, there is increasing recognition that the effectiveness even of apparently simple interventions is often influenced by complex interplays of individual characteristics, social determinants, the health care delivery system, and the interventions themselves. Systematic reviews of topics, such as slum upgrading [1,2], behavioral interventions for autism [3,4], smoking cessation in pregnancy [5], and the integration of mental health in primary care [6,7], illustrate that the boundaries of traditional reviews and review methods are being expanded and that reviewers are in need of guidance and tools to address this new approach.

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.

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)0.140
metaresearch head score (Gemma)0.477
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.799
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1400.477
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0140.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.979
GPT teacher head0.808
Teacher spread0.172 · 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