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Record W3203449392 · doi:10.1016/s2666-7568(21)00201-4

Not a disease: a global call for action urging revision of the ICD-11 classification of old age

2021· article· en· W3203449392 on OpenAlexaff
Debanjan Banerjee, Sanchari Mukhopadhyay, Kiran Rabheru, Gabriel Ivbijaro, Carlos Augusto de Mendonça Lima

Bibliographic record

VenueThe Lancet Healthy Longevity · 2021
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of OttawaInternational Development Research Centre
Fundersnot available
KeywordsScopusDiseaseGerontologyPrivilege (computing)Population ageingPopulationVulnerability (computing)MedicineDemographyPsychologyMEDLINEPolitical sciencePathologySociologyEnvironmental healthComputer science

Abstract

fetched live from OpenAlex

The inclusion of old age in the 11th revision of the International Classification of Diseases (ICD-11) under general symptoms (code MG2A) and in the causality section of XT9T,1 has been justified by arguing that old age brings about several biological changes of vulnerability.2 We argue that simply equating old age as a disease in the ICD-11 is potentially detrimental and deleterious from clinical, research, and humanitarian points of view, and propose alternate productive solutions.

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)0.065
metaresearch head score (Gemma)0.124
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.065
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.124
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0090.009
Science and technology studies0.0030.009
Scholarly communication0.0080.016
Open science0.0070.010
Research integrity0.0100.034
Insufficient payload (model declined to judge)0.0120.007

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 head0.113
GPT teacher head0.391
Teacher spread0.279 · 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
GenreCommentary

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

Citations13
Published2021
Admission routes1
Has abstractyes

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