MétaCan
Menu
Back to cohort
Record W2266133697 · doi:10.1177/1010539515616454

Community-Based Study on Family-Related Contributory Factors for Childhood Unintentional Injuries in an Urban Setting of Sri Lanka

2015· article· en· W2266133697 on OpenAlexaff
Dhanusha Punyadasa, Diana Samarakkody

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2015
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsSpinal Cord Injury BC
FundersFogarty International Center
KeywordsMedicineSri lankaIncidence (geometry)Cross-sectional studyInjury preventionUrban communityDemographyPediatricsPoison controlEnvironmental healthGeography

Abstract

fetched live from OpenAlex

A community-based descriptive cross-sectional study was carried out among children aged 1 to 4 years residing in an urban setting of Sri Lanka to assess the incidence and associated family-related factors of unintentional injuries. A total of 458 children were recruited using simple random sampling technique, giving a response rate of 91.6%. The incidence of unintentional injuries that needed medical attention during the study period of 3 months was 28.1 per 100 children (95% CI = 19.46-36.74). The factors that were significantly associated with the occurrence of unintentional injuries among children are low monthly income of the family (P = .045), low social support to the mother of index child (P = .022), nonauthoritative type of parenting of the mother of index child (P = .039), cared by person other than mother during day time (P = .002), frequent arguments between parents (P = .004), and frequent alcohol consumption of father (P = .001).

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 score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.116
GPT teacher head0.389
Teacher spread0.273 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueAsia Pacific Journal of Public HealthSame topicInjury Epidemiology and PreventionFrench-language works237,207