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Record W2266777921

Acute adult and adolescent poisoning in Tehran, Iran; the epidemiologic trend between 2006 and 2011.

2014· article· en· W2266777921 on OpenAlexaff
Hossein Hassanian‐Moghaddam, Nasim Zamani, Mitra Rahimi, Shahin Shadnia, Abdolkarim Pajoumand, Saeedeh Sarjami

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsMedicineOpiumPoison control centerNarcoticHeroinSubstance abuseDrug overdosePoison controlInjury preventionEmergency medicinePsychiatryPediatricsDrugHistory
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to determine the frequency of each poisoning and its related death in our center as a sample of Tehran in six consecutive years (2006 to 2011). METHODS: All poisoned children and adults referring to Loghman-Hakim hospital poison center and hospitalized in the study period were enrolled and evaluated. RESULTS: In 108,265 patients, the most common causes of poisoning were anti-epileptics and sedative-hypnotics (22.3%). The most common causes of death were pesticides (24.84%) and narcotics (24.75%). In drugs of abuse, opium was more prevalent in the early period of the study but was replaced by methadone later. CONCLUSION: It seems that national policies for drug control and prevention of suicide have not been efficient enough. We expect to see Iran in the first 50 countries with regard to suicide and to maintain the first place in narcotic abuse if enough attention is not provided.

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)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.035
GPT teacher head0.264
Teacher spread0.229 · 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

Citations96
Published2014
Admission routes1
Has abstractyes

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