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Record W2101970158 · doi:10.1186/1749-7922-7-s1-s5

Fatal motorcycle crashes: a serious public health problem in Brazil

2012· article· en· W2101970158 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.

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

Bibliographic record

VenueWorld Journal of Emergency Surgery · 2012
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsMedicineInjury preventionBlood alcoholOccupational safety and healthPoison controlMedical emergencyEmergency medicineInjury Severity ScoreSuicide preventionHuman factors and ergonomics

Abstract

fetched live from OpenAlex

INTRODUCTION: The numbers of two-wheel vehicles are growing across the world. In comparison to other vehicles, motorcycles are cheaper and thus represent a significant part of the automobile market. Both the mobility and speed are attractive factors to those who want to use them for work or leisure. Crashes involving motorcyclists have become an important issue, especially fatal ones. Specific severe injuries are responsible for the deaths. Defining them is necessary in order to offer better prevention and a more suitable medical approach. METHODS: All fatal motorcycle crashes between January 2001 and December 2009 in Campinas, Brazil, were analyzed in this study. Official data have been collected from police incident reports, hospitals' registers and autopsies. Both incidents and casualties were analyzed according to relevant variables. The Injury Severity Score (ISS) was calculated, describing the most potentially fatal injuries. RESULTS: There were 479 deaths; 90.8% were male; the mean age was 27.8 (range 0-73); 86.4% were conductors of the vehicles; blood alcohol was positive in 42.3%; 49.7% died at a hospital; 32.6% died at the scene; 26.1% of the accidents occurred at night, 69.1% were urban and 30.9% occurred on highways. The main causes of injury were collisions (63%) and falls (14%). The mean ISS was 38.5 (range 9-75). With regard to injuries, head trauma (67%) and thoracic trauma (40%) were the most common, followed by abdominal trauma (35%). Traumatic brain injury (67%) and hypovolemic shock (38%) were the most frequent causes of death. CONCLUSIONS: Alcohol was a significant factor in relation to the accidents. Head trauma was the most frequent and severe injury. Half of the victims died before receiving adequate medical attention, suggesting that prevention programs and laws should be implemented and applied in order to save future lives.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.036
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.070
GPT teacher head0.365
Teacher spread0.295 · 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