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Record W2153755601 · doi:10.1111/1556-4029.12261

Fatalities Due to Indigenous and Exotic Species in Florida

2013· article· en· W2153755601 on OpenAlexaff
Barbara C. Wolf, Brett E. Harding

Bibliographic record

VenueJournal of Forensic Sciences · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsIndigenousCoronerPoison controlWildlifePopulationEnvenomationMedical examinerMedicineInjury preventionAsphyxiaMedical emergencyEnvironmental healthFisheryEcologyBiology

Abstract

fetched live from OpenAlex

Florida's climate is suitable for many potentially hazardous animals, including both indigenous and exotic species, which are frequently kept as in zoos or as pets. This has resulted in many unforeseen fatal encounters between animals and the ever expanding human population. While the literature and knowledge pool for more common types of deaths referred to medical examiner/coroner's offices is abundant, the appreciation of wildlife and exotic pet-related deaths is far less widespread. We report seven animal attack-related deaths that occurred in Florida. The inflicted injuries included blunt and sharp force injuries, asphyxia, drowning, and envenomation. The underlying cause of death, however, was always a result of the human/animal interaction and in many cases related to human error and failure to appreciate the potentially dangerous behavior of nondomesticated species. These cases illustrate the varied circumstances and pathophysiologies associated with deaths due to indigenous and exotic species and the importance of the multidisciplinary approach in the medicolegal investigation of these cases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2013
Admission routes1
Has abstractyes

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