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Perfil da mortalidade por intoxicação com medicamentos no Brasil, 1996-2005: retrato de uma década

2012· article· pt· W2084898977 on OpenAlexaff
Daniel Marques Mota, José Romério Rabelo Melo, Daniel Roberto Coradi de Freitas, Márcio Machado

Bibliographic record

VenueCiência & Saúde Coletiva · 2012
Typearticle
Languagept
FieldSocial Sciences
TopicPublic Health in Brazil
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineChristian ministryEpidemiologyPublic healthMortality rateDescriptive statisticsEnvironmental healthDemographySurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

The occurrence of deaths caused by intoxication with medication have been considered a worsening public health problem. The study describes the epidemiological profile of medication-related intoxication in the general Brazilian population from 1996 to 2005. A descriptive study was conducted with mortality data obtained from the Mortality Information System of the Brazilian Ministry of Health. Deaths were selected according to the codes of the International Classification of Diseases (ICD-10). A total of 4,403 deaths were found inn males (53.9%), bachelors (53.7%) and the 20 to 39 year-old age bracket (44%). The majority of deaths were caused by intentional self-intoxication using anticonvulsants, sedatives, antiparkinsonians and psychotropics. The standardized mortality rate was higher in the Midwest region and Potential Life-Years Lost increased by 15.5%. The study showed the characteristics and variations in mortality by intoxication with medication in Brazil, which can be a reflex of the medication consumption patterns of the country, indicating the need for enhancement of sanitary vigilance policies.

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)0.002
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 score0.077
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.050
GPT teacher head0.357
Teacher spread0.307 · 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

Citations53
Published2012
Admission routes1
Has abstractyes

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