MétaCan
Menu
Back to cohort
Record W4247905031 · doi:10.14283/jfa.2021.34

Symposia — Conferences — Oral Communications

2021· article· en· W4247905031 on OpenAlexaboutno aff

Bibliographic record

VenueThe Journal of Frailty & Aging · 2021
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsSarcopeniaMedicineGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Background: A growing number of older people reside in long-term care (LTC) homes. As they near the end-of-life, it is vital that LTC residents express their healthcare wishes though Advance Care Planning (ACP). Yet, ACP remains suboptimal and LTC residents often experience unmet needs and unnecessary hospital transfers. Objectives: We applied the Knowledge-To-Action framework to 1) identify shared barriers and solutions to improve the process of ACP and end-of-life care for LTC residents; 2) develop a standardized, scalable, and person-centered approach to ACP, and 3) evaluate this approach in a multicentre cluster randomized trial. Methods: We began in September 2017 with a 1-day workshop for 44 LTC stakeholders, including residents and families, from Manitoba, Alberta, and Ontario. Sessions were recorded and thematic analysis performed. An environmental scan was conducted to assess ACP practices in 38 LTC homes in participating provinces. Over the following 11 months, we developed the intervention to address weak links in ACP. From August 2018 to August 2020, we conducted an unblinded, cluster-randomized, mixed-methods trial in 29 LTC homes (15 intervention, 14 control) in these provinces to assess the impact of the intervention on ACP comprehensiveness and care and interventions at the end-of-life (ClinicalTrials.gov NCT03649191). Results:

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.709
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.164
GPT teacher head0.418
Teacher spread0.254 · 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 teacher head, 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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Frailty & AgingSame topicNutrition and Health in AgingFrench-language works237,207