MétaCan
Menu
← Back to cohort
Record W6991246549

Feature Story: First class of nurses graduate and helping healthcare

2015· other· en· W6991246549 on OpenAlexaboutno aff

Bibliographic record

VenueoURspace (University of Regina) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorGraduation (instrument)First classHealth careFeature (linguistics)Class (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Saskatchewan now has more nurses, following the graduation of 170 new nurses through the Saskatchewan Collaborative Bachelor of Science in Nursing program, offered by the University of Regina and Saskatchewan Polytechnic. Now that they have earned their degrees, these new nurses are applying what they’ve learned by starting their careers in hospitals and health care facilities across the province. This year’s Spring Convocation held special significance for the Faculty of Nursing, because the first cohort of students in the SCBScN program graduated. This collaborative program began in the fall of 2011, with graduates earning University of Regina degrees.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.188
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0130.002
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0950.024

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 head0.029
GPT teacher head0.241
Teacher spread0.211 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueoURspace (University of Regina)→French-language works237,207→