MétaCan
Menu
Back to cohort
Record W3049001788 · doi:10.1093/jme/tjaa148

A Review of Black Widow (Araneae: Theridiidae) Envenomation, Epidemiology, and Antivenom Utilization in Canada

2020· review· en· W3049001788 on OpenAlexaffabout
Gwynn Curran-Sills, Steven M. Wilson, Robb Bennett

Bibliographic record

VenueJournal of Medical Entomology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVenomous Animal Envenomation and Studies
Canadian institutionsRoyal British Columbia MuseumCanadian Armed ForcesUniversity of Calgary
Fundersnot available
KeywordsEnvenomationTheridiidaeAntivenomNova scotiaEpidemiologyBiologyMedicineEcologySpiderGeographyVenomInternal medicineArchaeology

Abstract

fetched live from OpenAlex

Two species of black widow spider (BWS-Latrodectus hesperus Chamberlin & Ivie and Latrodectus variolus Walckenaer) naturally occur in Canada and are capable of causing deleterious envenomation to humans. No Canadian literature exists on the frequency of envenomations by these species or the use of antivenom in the treatment of those patients. A review of primary Canadian arachnology data was undertaken to identify BWS populations. A retrospective review of the Health Canada Special Access Program records generated epidemiology and the utilization of antivenom for BWS envenomations in Canada. The geographical distribution of BWS species is limited to along the southern Canadian border. From January 2009 to December 2015, there were five BWS envenomations that required treatment with antivenom and all cases occurred in British Columbia. An average patient age of 41 yr ± 21 SD (range 7-59) was observed, along with three of the five patients being female. The average number of vials used for treatment was 2 ± 1 SD (range 1-3). BWS Antivenin was also obtained by facilities in Alberta, Ontario, and Nova Scotia, but not used in any of these jurisdictions. Further investigation is necessary to determine the annual incidence of BWS envenomations and if treatment with BWS antivenin is required.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.068
GPT teacher head0.365
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Medical EntomologySame topicVenomous Animal Envenomation and StudiesFrench-language works237,207