MétaCan
Menu
Back to cohort
Record W3017884540 · doi:10.1111/edt.12562

Dental and maxillofacial injuries associated with electric‐powered bikes and scooters in Israel: A report for 2014‐2019

2020· article· en· W3017884540 on OpenAlex
Shaul Lin, Sharon Goldman, Kobi Peleg, Liran Levin

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

VenueDental Traumatology · 2020
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineEngineeringDentistryForensic engineering

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Electric-Powered Bikes and powered scooters present a new method of transportation and are becoming commonly used worldwide. However, the reports on traumatic dental injuries related to their use are scarce. The aim of this study was to report the frequency and severity of dental and maxillofacial injuries associated with electric-powered bikes and scooters in Israel between the years 2014 and 2019. METHODS: This was a retrospective cohort study based on data from the Israeli National Trauma Registry (INTR). The INTR provides comprehensive data on hospitalized patients from all six Level I trauma centers (TC) and 15 of the 20 Level II TCs in Israel. All injured patients who were hospitalized due to a traffic collision between 2014 and 2019 were identified. The data for those hospitalized due to an e-bike or motorized scooter accident were extracted as well as for pedestrians who were injured as a result of a crash with these vehicles. RESULTS: A total of 3,686 hospital admissions were related to electric-powered bikes and scooters. Of those, 378 (10.3%) were oral and maxillofacial injuries. Most of the oral and maxillofacial injuries were attributed to powered bikes (321 out of 378; 84.92%) and the rest to powered scooters. There was a constant increase in general as well as the oral and maxillofacial injuries during the study years. Almost 20% of the cases involved injuries to the teeth. Overall, 291 pedestrians were reported to be injured due to electric-powered bikes and scooters; 29 (9.97%) of them, suffered from oral and maxillofacial injuries. Most of those were children aged 0-15 years (41.38%) and elders older than 60 years (37.39%). CONCLUSIONS: Trauma related to electric-powered bikes and scooters is an increasing concern. Dental professionals should be actively involved in educational and legislative efforts focusing on the prevention of e-bike and scooter-related injuries, in general, and specifically maxillofacial injuries.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.529

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)0.0000.000

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 head0.019
GPT teacher head0.303
Teacher spread0.284 · 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