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Record W2163273095 · doi:10.12927/cjnl.2002.19163

Canadian Forces Seek Out Civilian Nurses For Case Managers

2002· article· en· W2163273095 on OpenAlexaffvenueabout
R Carefoote

Bibliographic record

VenueNursing leadership · 2002
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsCanadian Armed Forces
Fundersnot available
KeywordsNursingHealth careCase managementMilitary personnelPsychologyPublic relationsMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

This article describes a novel case management program implemented by the Canadian Forces Health Services to care for its ill and injured members. A brief overview of the military environment is followed by the reasons why the military looked to the civilian sector and selected case management as a strategy for its continuity of care issues. Principles guiding the design and operations of the program are highlighted along with a description of the core case management activities. Staff roles are outlined including the reasoning behind hiring baccalaureate prepared civilian nurses as Case Managers. The article ends with a description of its current status and notes that preliminary member satisfaction findings demonstrate that nurses are making a positive difference in lives of soldiers that are ill or injured.

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)0.002
metaresearch head score (Gemma)0.007
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: Other
Teacher disagreement score0.374
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.002
Scholarly communication0.0040.001
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0330.004

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 head0.433
Teacher spread0.054 · 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

Citations1
Published2002
Admission routes3
Has abstractyes

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