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Record W3025167951 · doi:10.1503/cjs.015118

Novel use of FaceTime video calling in a deployed setting to assist with the care of a military working dog

2018· article· en· W3025167951 on OpenAlexaffvenueabout
Benjamin Donham, Megan Lee Wickett

Bibliographic record

VenueCanadian Journal of Surgery · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSpecialtyMedical emergencyCritically illPrioritizationUnit (ring theory)Medical careTransmission (telecommunications)NursingFamily medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Summary: In deployed settings, veterinary recourses are limited and nonveterinary medical providers frequently are required to provide medical treatment to military working dogs (MWDs) until veterinary specialty care can be provided. We present the case of a critically ill MWD who presented initially to a Canadian NATO Role II facility in Iraq that lacked immediate veterinary support. Through the use of FaceTime interactive video calling, the Role II medical providers were able to consult with the MWD unit’s veterinarian in the United States and provide effective evaluation, treatment and prioritization of medical evacuation (MEDEVAC). FaceTime video calling was extremely effective and should be considered in future situations where specialist care is not immediately available and transmission of visual information would be beneficial.

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)0.000
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 score0.135
Threshold uncertainty score0.877

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 head0.046
GPT teacher head0.292
Teacher spread0.247 · 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 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

Citations8
Published2018
Admission routes3
Has abstractyes

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