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Record W2516899970

ANALYSIS OF SOME EPIDEMIOLOGICAL RATES OF SUICIDE IN GEORGIA.

2016· article· en· W2516899970 on OpenAlexaff
L Kiladze, G Lezhava, E Gadelia

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsChristian ministryEpidemiologySuicide preventionSuicide ratesPoison controlInjury preventionMedical emergencyHuman factors and ergonomicsData collectionEnvironmental healthStatistical analysisOccupational safety and healthMedicineIncidence (geometry)DemographyPsychologyStatisticsPolitical scienceMathematicsSociologyPathology
DOInot available

Abstract

fetched live from OpenAlex

In the last few years, significant increase in the incidence of suicide is observed in Georgia, especially among teenagers. Effectiveness of suicide prevention greatly depends on adequate determination of causes of suicide. Statistics of suicidal death and attempts in Georgia are recorded in two agencies: the National Statistics Office (GeoStat) and the Ministry of Internal Affairs of Georgia (MIA). Data from both agencies - main epidemiological indicators of 2011 - 2014 have been statically processed, analyzed and compared with the WHO data. Conducted research revealed significant difference between data obtained from the GeosStat and the MIA that may be the cause of absence of complete, unified system. Besides, the data are substantially different from the WHO-recognized findings. Therefore, specification of suicide's substantive criteria and improvement of the statistical data collection methodology are necessary that require joint and coordinated actions of several agencies.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.345
Teacher spread0.252 · 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 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".

Quick stats

Citations2
Published2016
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicSuicide and Self-Harm Studies→French-language works237,207→