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Record W2883418130 · doi:10.5430/jnep.v8n12p45

Transitioning psychiatric patients for positive outcomes

2018· article· en· W2883418130 on OpenAlexvenueno aff
Janice Dennis, Delois Long

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Operations and Scheduling Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyTowerAsset (computer security)Depression (economics)PsychiatryCapital (architecture)PsychologyMedicineComputer securityEngineeringComputer scienceEconomicsArtVisual arts

Abstract

fetched live from OpenAlex

A study was conducted at the Louis Stokes Cleveland Veterans Administration Medical Center (LSCVAMC) to examine if moving 20 psychiatric patients from one location to another affected their anxiety level. The LSCVAMC closed their Brecksville facility to consolidate the two Branches (Wade Park and Brecksville), and build a new Capital Asset Realignment for Enhanced Services (CARES) Tower. These changes were implemented to reduce operating costs for LSCVAMC and reduce the number of inpatient psychiatric beds. A five-question survey was given to each patient one week prior to the move, and immediately following the move to assess their thoughts related to the move. The results showed that despite 45% expressing thoughts that the move to Wade Park made them nervous/anxious prior to the move, no patients expressed that they were anxious post move when asked. Eighty percent of the patients expressed that they would enjoy being in a newly renovated facility. The post report of the patients was no nervousness/anxiety related to the move.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.130
GPT teacher head0.560
Teacher spread0.430 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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