MétaCan
Menu
Back to cohort
Record W2913947001 · doi:10.17605/osf.io/gvr7y

Understanding collaborative approaches to research: A synthesis of the research partnership literature

2018· article· en· W2913947001 on OpenAlexaffabout
Heather L. Gainforth, Tram Nguyen, Femke Hoekstra, Kelly Mrklas, Christine Neilson, Mathew Vis‐Dunbar, Kathryn M. Sibley

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeneral partnershipEngineering ethicsManagement sciencePolitical scienceSociologyKnowledge managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

A Coordinator Multicenter Team approach describing a series of complementary literature reviews conducted across six Canadian universities, exploring unique aspects of different types of research partnership approaches, predominantly in the health sciences.

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)0.159
metaresearch head score (Gemma)0.205
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.841
Threshold uncertainty score0.840

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1590.205
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0370.046
Science and technology studies0.0130.014
Scholarly communication0.0380.023
Open science0.0040.014
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.793
GPT teacher head0.531
Teacher spread0.261 · 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.

Study designSystematic review
DomainMethods
GenreReview

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

Citations5
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueOSF Preprints (OSF Preprints)Same topicEvaluation and Performance AssessmentFrench-language works237,207