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Record W2158218717 · doi:10.1177/0009922814526977

Serious Impact of Handlebar Injuries

2014· article· en· W2158218717 on OpenAlex
Hannah Cherniawsky, Ioana Bratu, Tara Rankin, William Sevcik

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Pediatrics · 2014
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsStollery Children's HospitalUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaUniversity of AlbertaPublic Health Agency of Canada
KeywordsMedicinePoison controlInjury preventionHuman factors and ergonomicsSuicide preventionOccupational safety and healthMedical emergencyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Injuries from bicycles is a leading cause of trauma in children. We sought to investigate the epidemiology of bicycle handlebar injuries. METHODS: A retrospective analysis of bicycle trauma treated at our institution was preformed. RESULTS: A total of 462 children younger than 17 years had bicycle trauma. Abdominal handlebar injuries, representing 9% of bicycle injuries, contributed to 19% of all internal organ injuries, and 45.4% of solid, 87.5% of hollow, 66.6% of vascular or lymphatic, and 100% of pancreatic injuries. Handlebar injuries were 10 times more likely to cause severe injury, yet more than half of the children were misdiagnosed at their initial presentation. Delayed diagnosis and longer hospital stays were observed in handlebar injuries to the abdomen. CONCLUSION: Physicians should be aware of the serious impact of bicycle handlebar injury to the abdomen. The mechanism alone should raise the suspicion of internal organ injury, and timely imaging and surgical consultation.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.027
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.037
GPT teacher head0.415
Teacher spread0.378 · 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