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Record W2598074818 · doi:10.1590/0102-3772e32ne216

Usuários de Crack que Buscam Tratamento em Brasília

2016· article· pt· W2598074818 on OpenAlexaff
Maria Inês Gandolfo Conceição, Hannya Herrera Cardona, Jaqueline Tavares de Assis, Rebeca Rocha Mohr, María Fátima Olivier Sudbrack, Carol Strıke

Bibliographic record

VenuePsicologia Teoria e Pesquisa · 2016
Typearticle
Languagept
FieldSocial Sciences
TopicYouth, Drugs, and Violence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyDepression (economics)HumanitiesPhysicsGerontologyMedicinePhilosophyEconomics

Abstract

fetched live from OpenAlex

RESUMO Objetivando identificar o perfil de pacientes ambulatoriais que procuram tratamento para problemas relacionados com crack em Brasília, 132 usuários que recebem serviços psicológicos preencheram o Questionário sobre o Perfil de Consumo de Crack e o Cocaine Craving Questionnaire-Brief. Os participantes eram homens (83,6%), solteiros (38,8%) e possuíam residência (100%). O primeiro uso foi motivado pela curiosidade (65,9%), influência dos pares (58,3%) e fácil acesso (50,8%). A maioria (65,2%) relatou poliuso. O mais longo período de abstinência foi de quatro anos (1,5%) e a maioria (46%) relatou menos de 30 dias. O poder letal, dependência e contextos de vulnerabilidade social associados ao crack foram questionados neste estudo. São necessários esforços para melhor atender aos que não acessam o sistema de tratamento.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.286
Threshold uncertainty score0.569

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.323
Teacher spread0.284 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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