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Record W6986449332

Populating an Indicator of Serious Paediatric Fall Injuries across Age and Public Health Units in Ontario

2022· other· en· W6986449332 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueYork University Digital Library (York University) · 2022
Typeother
Languageen
FieldSocial Sciences
TopicEvasion and Academic Success Factors
Canadian institutionsnot available
Fundersnot available
KeywordsInjury preventionPoison controlOccupational safety and healthPublic healthFalling (accident)Suicide preventionPopulation
DOInot available

Abstract

fetched live from OpenAlex

Fall injuries among children and youth represent a significant burden to public health. Currently, there is no indicator assessing serious fall injuries in children. The purpose of this study was to populate an indicator of serious fall injuries within the paediatric population (0-19 years) using existing ICD-10 coded hospitalization data. The Discharge Abstract Database was used to examine all fall-related hospitalizations in Ontario from 2010-2019. Rates per 100,000 population and rate ratios were calculated for all fall-related and serious fall injuries; serious falls accounted for 3,652 hospitalizations. The highest rates for all fall-related and serious fall injuries were reported in rural health units. The mechanisms of serious fall injuries were highest among males 10-14 and 15-19 from skis, blades, skates, and boards, whereas rates were highest among females 0-4 from stairs and 5-9 from playgrounds. This indicator can be used to prompt action to reduce serious fall injuries in children.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.237
Teacher spread0.200 · 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