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Record W4318054413 · doi:10.3390/nursrep13010015

A Call for Urgent Action: Innovations for Nurse Retention in Addressing the Nursing Shortage

2023· editorial· en· W4318054413 on OpenAlexaff
Sonia Udod

Bibliographic record

VenueNursing Reports · 2023
Typeeditorial
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWorkforceCall to actionNursingEconomic shortagePandemicCoronavirus disease 2019 (COVID-19)Action (physics)Health careNursing shortage2019-20 coronavirus outbreakHealthcare deliveryBusinessMedicinePsychologyPolitical scienceNurse educationMarketingVirology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has become a defining moment for healthcare delivery and the health workforce despite "being prepared" for it [...].

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)0.025
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.050
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.076
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0040.002
Science and technology studies0.0070.006
Scholarly communication0.0130.011
Open science0.0070.003
Research integrity0.0500.063
Insufficient payload (model declined to judge)0.0140.012

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 head0.213
GPT teacher head0.543
Teacher spread0.330 · 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
GenreEditorial

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

Citations10
Published2023
Admission routes1
Has abstractyes

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