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Record W2732317649 · doi:10.1093/geroni/igx004.4582

LNTRODUCTION OF ISUPPORT: DESIGN AND CONTENT

2017· article· en· W2732317649 on OpenAlexaboutno aff
Anne Margriet Pot

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsPresentation (obstetrics)Adaptation (eye)Mental healthResource (disambiguation)DementiaComputer scienceMedical educationPsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

This first presentation provides more details on the design of iSupport, the way in which the program works, and how the World Health Organization (WHO) supports adaptation and implementation in different resource settings. The generic field-testing version of iSupport consists of 5 modules: Introduction to dementia, Being a caregiver, Providing everyday care, Caring for me and Dealing with Challenging Behaviours. These modules contain 23 interactive lessons in total, all based on small exercises with feedback. An adaptation and implementation guide for countries is available. The iSupport program has been developed by WHO in collaboration with the Netherlands Institute on Mental Health and Addiction and many experts from around the world, including experts from Stanford University (U.S.), NIMHANS (India), and the University of Calgary (Canada), who will give the next presentations.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score0.180

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 communication0.0000.001
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 head0.128
GPT teacher head0.310
Teacher spread0.182 · 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 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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