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Record W1488303669 · doi:10.1109/cbms.1992.244945

Nursing workload management for a patient data management system

2003· article· en· W1488303669 on OpenAlexafffundabout
K. Roger, Christine Collet, N. Fumai, M. Petroni, A.S. Malowany, Franco A. Carnevale, Ronald Gottesman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsMontreal Children's HospitalMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWorkloadIBMScheduleNursing managementComputer scienceSession (web analytics)IBM PC compatibleNursingOperating systemMedicineWorld Wide WebSoftware

Abstract

fetched live from OpenAlex

A new bedside data entry system is being developed for the patient data management system at the Pediatric Intensive Care Unit of the Montreal Children's Hospital. Part of this development is the addition of a nursing workload manager (NWM) to help plan and document the nurses' workload. The NWM has four main functions: generate nursing care plans, automate workload measurement scoring, schedule nursing activities, and set up fluid balance charts by integrating with a fluid balance module. The design and operation of the NWM are presented. The implementation of the nursing care plan generation and workload measurement scoring is detailed along with the results of a user evaluation session. The application was developed using IBM's OS/2 Presentation Manager window environment.>

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.079
GPT teacher head0.357
Teacher spread0.278 · 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 designObservational
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

Citations2
Published2003
Admission routes3
Has abstractyes

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