MétaCan
Menu
Back to cohort
Record W4400358242 · doi:10.12968/bjca.2024.0034

CONNECTing nurses and allied professionals through a cardiac surgery masterclass programme

2024· article· en· W4400358242 on OpenAlexaff
Tracey Bowden, Jill Bruneau, Yingyan Chen, Suzanne Fredericks, Maria Hayes, Rosalie Magboo, Sheila O’Keefe-McCarthy, Rafaela Batista dos Santos Pedrosa, Karen L. Then, Richard van Valen

Bibliographic record

VenueBritish Journal of Cardiac Nursing · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of CalgaryBrock UniversityToronto Metropolitan UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineHealth professionalsMedical educationNursingHealth care

Abstract

fetched live from OpenAlex

CONNECT is a network of nursing and allied professional researchers, focused on strengthening collaborative cardiac surgery research through shared initiatives. In the third instalment of this five-article series, the authors introduce a CONNECT masterclass programme, aiming to meet the clinical and research development needs of nurses and allied professionals working in cardiac surgery.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBritish Journal of Cardiac NursingSame topicCardiac, Anesthesia and Surgical OutcomesFrench-language works237,207