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Record W4225107271 · doi:10.1097/nnd.0000000000000835

Elevating the Preceptor Role

2022· article· en· W4225107271 on OpenAlexaff
Sarah N. Hardacker, Madeline Perkel, Karen E. King, Larissa Hutchins

Bibliographic record

VenueJournal for Nurses in Professional Development · 2022
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsPreceptorPsychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

Hardacker, Sarah MSN, RN, NPD-BC; Perkel, Madeline Masucci MSN, NPD-BC, CHSE; King, Karen MSN, RN-BC, NEA-BC; Hutchins, Larissa RN, DNP, CCRN-K, CCNS, NEA-BCEditor(s): Bodine, Jennifer DNP, FNP-C, NPD-BC, CEN Author Information

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)0.005
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0760.021

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 head0.019
GPT teacher head0.350
Teacher spread0.331 · 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
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

Citations6
Published2022
Admission routes1
Has abstractyes

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