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Record W4306158116 · doi:10.1177/00084174221123721

Rapid Reviews to Support Practice: A Guide for Professional Organization Practice Networks

2022· article· en· W4306158116 on OpenAlexvenueaboutno aff
Megan MacPherson, Rosalie H. Wang, Emma Smith, Gobika Sithamparanathan, Cara A. Sadiq, Anna RH Braunizer

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsSystematic reviewProcess (computing)Clinical PracticeEvidence-based practiceOccupational therapyHealth careMechanism (biology)Management scienceKnowledge managementPsychologyMEDLINEMedicineMedical educationAlternative medicineComputer scienceNursingPolitical scienceEngineeringPsychiatry

Abstract

fetched live from OpenAlex

Background. Occupational Therapists, among other healthcare decision makers, often need to make decisions within limited timeframes and cannot wait for the completion of large rigorous systematic reviews and meta-analyses. Rapid reviews are one method to increase the integration of research evidence into clinical decision making. Rapid reviews streamline the systematic review process to allow for the timely synthesis of evidence; however, there does not exist a single agreed upon guide for the methodology and reporting of rapid reviews. Purpose. This paper proposes a rapid review methodology that is customized to a professional organization practice which can feasibly be used by practice networks such as those of the Canadian Association for Occupational Therapy to conduct reviews. Implications. Practice networks provide a sustainable mechanism to integrate research evidence and foster communication amongst practitioners. This guide for conducting and reporting rapid reviews can be used across Occupational Therapy practice networks and similar groups to support the consistent and timely synthesis of evidence necessary to improve evidence-informed clinical decision making.

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 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)0.010
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.202
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.291
GPT teacher head0.549
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
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

Citations12
Published2022
Admission routes2
Has abstractyes

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