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Record W2053932671 · doi:10.1001/jama.2010.616

Global Mental Health

2010· article· id· W2053932671 on OpenAlexfundno aff
Vikram Patel, Martin Prince

Bibliographic record

VenueJAMA · 2010
Typearticle
Languageid
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersUniversity of Cape TownNational Institute of Mental HealthUniversity of TorontoWellcome Trust
KeywordsMedicineMental healthGlobal healthField (mathematics)Global mental healthPsychiatryPublic healthNursing

Abstract

fetched live from OpenAlex

LOBAL HEALTH IS “AN AREA FOR STUDY, RESEARCH and practice that places a priority on improving healthandachievingequityinhealthforallpeople worldwide.” 1 Global mental health is the application of these principles to the domain of mental ill health. The most striking inequity concerns the disparities in provision of care and respect for human rights of persons living with mental disorders between rich and poor countries. Low- and middle-income countries are home to more than 80% of the global population but command less than 20% of the share of the mental health resources. 2 The consequent “treatment gap” is a contravention of basic human rights—morethan75%ofthoseidentifiedwithseriousanxiety, mood, impulse control, or substance use disorders in the World Mental Health surveys in low- and middleincome countries received no care at all, despite substantialroledisability. 3 Insub-SaharanAfrica,thetreatmentgap forschizophreniaandotherpsychosescanexceed90%. 4 Even

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)0.001
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.209
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2090.045

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 head0.025
GPT teacher head0.396
Teacher spread0.371 · 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

Citations432
Published2010
Admission routes1
Has abstractyes

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