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Record W2765741775 · doi:10.5737/23688076274343347

Adaptation et utilisation du « modèle synergique » pour les patients hospitalisés à l’unité d’hématologie

2017· article· fr· W2765741775 on OpenAlexvenueno aff
Yayra Amenudzie, Γεωργία Γεωργίου, Enoch Ho, Elizabeth O’Sullivan

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2017
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGynecologyNuclear medicine

Abstract

fetched live from OpenAlex

Un projet pilote a été mis de l’avant par une unité de soins en hématologie et de greffes de cellules souches hématopoïétiques pour déterminer s’il est possible d’adapter le « modèle synergique » (Curley, 2007; 1998) à cette population de patients. Durant la phase 1, un outil de mesure des caractéristiques des patients portant sur la complexité, la stabilité, la prévisibilité et la participation aux soins a été développé et testé. Cet outil s’est révélé hautement valide et cohérent, et doté d’une validité conceptuelle et d’une concordance interévaluateurs modérée fort apparentes. Une évaluation de la compétence des infirmières a aussi été mise au point, ainsi que des procédures pour l’affectation des infirmières et des aides-soignants et un outil décisionnel pour la dotation. Les résultats de ce projet pilote démontrent que le modèle synergique peut être adapté à cette population et qu’il est possible de l’utiliser avec des patients hospitalisés.

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)0.033
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.204
GPT teacher head0.459
Teacher spread0.255 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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