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Record W2559596349 · doi:10.1097/pec.0000000000000965

Fracture and Nonaccidental Injury

2016· article· en· W2559596349 on OpenAlexaff
Helen Levin, Gurinder Sangha, Timothy P. Carey, Rodrick Lim

Bibliographic record

VenuePediatric Emergency Care · 2016
Typearticle
Languageen
FieldMedicine
TopicChild Abuse and Related Trauma
Canadian institutionsChildren's Hospital of Western OntarioLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineFracture (geology)Medical emergency

Abstract

fetched live from OpenAlex

Pediatric nonaccidental injury (NAI) is an important entity that is commonly seen in a variety of medical settings. These children often present to the emergency department or primary care physicians as the first point of contact after an NAI. There is a major risk associated with nonrecognition of an NAI, including a 35% chance of subsequent injury and a 5% to 10% risk of mortality. Therefore, it is essential for physicians to be vigilant when assessing injuries compatible with NAI, especially in infants and young children who are not able to independently express themselves. As fracture is the second most common manifestation of NAI, practitioners should be vigilant to recognize unusual fractures in atypical age ranges to aid in its diagnosis. Here, we present a novel case of a lateral condylar fracture in an almost 13-month-old-child that has not been previously associated with NAI.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.247
Teacher spread0.243 · 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 teacher head, not a consensus.

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

Citations2
Published2016
Admission routes1
Has abstractyes

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