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Record W4321766392 · doi:10.1016/j.ijnss.2023.02.002

Corrigendum to “Exploring social movement concepts and actions in a knowledge uptake and sustainability context: A concept analysis” [Int J Nurs Sci 9/4 (2022) 411–421]

2023· erratum· en· W4321766392 on OpenAlexaff
Doris Grinspun, Katherine Wallace, Shelly‐Anne Li, Susan McNeill, Janet E. Squires, Jesús Bujalance Hoyos, Maryanne D’Arpino, Gina De Souza, Nataly Farshait, John Gabbay, Ian D. Graham, Alison M. Hutchinson, Kim Kinder, Celia Laur, Tina Mah, Julia E. Moore, Jennifer Plant, Jodi Ploquin, P. James A. Ruiter, Daphney St‐Germain, Margie Sills-Maerov, May Lin Tao, Marita G. Titler, Junqiang Zhao

Bibliographic record

VenueInternational Journal of Nursing Sciences · 2023
Typeerratum
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsToronto Public HealthUniversité LavalQueensway-Carleton HospitalResearch Institute for AgingAlberta Health ServicesWomen's College HospitalUniversity of TorontoCARE CanadaOttawa HospitalUniversity of OttawaRegistered Nurses' Association of Ontario
Fundersnot available
KeywordsINTContext (archaeology)Movement (music)SustainabilitySociologyPsychologyComputer sciencePhilosophyGeography

Abstract

fetched live from OpenAlex

[This corrects the article DOI: 10.1016/j.ijnss.2022.08.003.].

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)0.006
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.089
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.076
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.003
Science and technology studies0.0070.004
Scholarly communication0.0060.004
Open science0.0050.005
Research integrity0.0120.016
Insufficient payload (model declined to judge)0.0700.048

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 head0.379
GPT teacher head0.565
Teacher spread0.186 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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