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Record W2019021634 · doi:10.1300/j186v03n02_05

Feeling Connected-Providing Computer Support, Access and Training to Patients in a Complex Continuing Care and Palliative Care Hospital

2003· article· en· W2019021634 on OpenAlexaff
Sharon A. Gigliotti

Bibliographic record

VenueJournal of Hospital Librarianship · 2003
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsOutreachFeelingPalliative careReferralNursingContinuing educationMedicinePlan (archaeology)Medical educationPsychology

Abstract

fetched live from OpenAlex

This article depicts the transformation of a traditional, staff-only library into a facility that promotes shared learning using technology for patients and families in a complex continuing care and palliative care hospital. The transition includes a new learning centre design and development of an outreach strategy, communication plan, integrated referral system, patient assessments and adaptations to meet physical needs, implementation of a teaching philosophy, and volunteer training. Individual patient stories illustrate how an interactive learning centre responds successfully to patient desires, their need to feel empowered and live a vital, engaged life in the hospital as home setting.

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)0.009
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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.003
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.090
GPT teacher head0.353
Teacher spread0.263 · 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 routes1
Has abstractyes

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