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Record W2885328908 · doi:10.5055/jem.2009.0028

The role of the psychiatric nurse practitioner in disaster response

2009· article· en· W2885328908 on OpenAlexaboutno aff
Brenda Marshall

Bibliographic record

VenueJournal of Emergency Management · 2009
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsnot available
Fundersnot available
KeywordsNursingQuarter (Canadian coin)Nurse practitionersMedicineHealth carePsychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Nurses have responded to, and prepared for disasters from the time of Florence Nightingale and Harriet Werley. Nurses are the largest group of professional healthcare providers in America with more than 2.4 million registered nurses, a quarter of a million of whom are Nurse Practitioners capable of diagnosing, prescribing, and treating patients. Psychiatric Nurse Practitioners are in a position to understand the unique cultural nuances and needs of a community in all phases of the disaster life cycle.

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)0.010
metaresearch head score (Gemma)0.030
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0070.002

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 head0.021
GPT teacher head0.387
Teacher spread0.366 · 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
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

Citations0
Published2009
Admission routes1
Has abstractyes

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