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Record W2017012032 · doi:10.1007/s11999-010-1565-4

The Epidemiology of Nonaccidental Trauma in Children

2010· review· en· W2017012032 on OpenAlex
Kishore Mulpuri, Bronwyn Slobogean, Stephen J. Tredwell

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2010
Typereview
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineEpidemiologyPediatric traumaPoison controlInjury preventionPediatricsMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Abuse of children is abhorrent in Western society and, yet, is not uncommon. Nonaccidental trauma (NAT) is the result of a complex sociopathology. Not all of the causative factors of NAT are known, many are incompletely described, not all function in each case, and many are secondary to preexisting pathology in other areas. QUESTIONS/PURPOSES: We therefore addressed the following questions in this review: (1) what is the general incidence of NAT; (2) what factors are intrinsic to the abused child, family, and society; and (3) what orthopaedic injuries are common in NAT? METHODS: We searched Medline, Medline In Process & Other Non-Indexed Citations, and Embase using OVID. Only one article fit our inclusion criteria; therefore, this is a descriptive generalized review of the epidemiology of NAT. RESULTS: The general incidence of NAT ranges from 0.47 per 100,000 to 2000 per 100,000. Younger children are at greater risk of NAT than older children. Parents are often the perpetrators of the abuse. Rib fractures are highly indicative of NAT in young children. CONCLUSIONS: It is important to consider child, family, and societal factors when confronted with suspicions of child abuse. Our review demonstrates the currently limited information on the true incidence of NAT. To determine a much more accurate incidence of NAT, there needs to be a population-based surveillance program conducted through primary care providers.

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)0.016
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0030.015
Insufficient payload (model declined to judge)0.0000.000

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 head0.199
GPT teacher head0.530
Teacher spread0.332 · 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