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Record W4401153700 · doi:10.3389/ijph.2024.1607247

Challenges and Solutions in Recruiting Older Vulnerable Adults in Research

2024· editorial· en· W4401153700 on OpenAlexafffund
Nadia Sourial, Jean‐Baptiste Beuscart, Łukasz Posłuszny, Matthieu Calafiore, Sónia S. Sousa, Esther Sansone, Marcelina Zuber, Isabelle Vedel

Bibliographic record

VenueInternational Journal of Public Health · 2024
Typeeditorial
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsJewish General HospitalUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de MontréalCentre for Advancing Health Outcomes
FundersHorizon 2020 Framework ProgrammeCanadian Institutes of Health ResearchEuropean Commission
KeywordsPublic healthGerontologyMedicineEnvironmental healthPsychologyNursing

Abstract

fetched live from OpenAlex

Nadia Sourial1,2*Jean-Baptiste Beuscart3Łukasz Posłuszny4Matthieu Calafiore5Sónia S. Sousa6Esther Sansone7Marcelina Zuber8Isabelle Vedel9,10 COVERAGE Collaborative Group

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)0.123
metaresearch head score (Gemma)0.346
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.877
Threshold uncertainty score0.648

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1230.346
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0060.003
Science and technology studies0.0070.006
Scholarly communication0.0170.013
Open science0.0070.004
Research integrity0.0270.032
Insufficient payload (model declined to judge)0.0080.007

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 head0.299
GPT teacher head0.492
Teacher spread0.193 · 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.

Study designNot applicable
DomainMethods
GenreEditorial

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

Citations4
Published2024
Admission routes2
Has abstractyes

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