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Record W2763480677 · doi:10.3389/fvets.2017.00165

Emergency and Critical Care Medicine: An Essential Component of All Specialties and Practices

2017· editorial· en· W2763480677 on OpenAlexaff
Karol A. Mathews

Bibliographic record

VenueFrontiers in Veterinary Science · 2017
Typeeditorial
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComponent (thermodynamics)Medicine

Abstract

fetched live from OpenAlex

Veterinary emergency and critical care medicine is one of the fastest growing specialties in veterinary medicine. Likened to two specialties joined as one, in a continuum of care and in a partnership working with other specialties, veterinary emergency and critical care focuses on the immediate needs of a severely ill or injured animal and also on management of the critical medical and surgical patient beyond the primary problem. A wide spectrum of illnesses, injuries, and toxicities ranging from acute kidney injury to snakebite and from severe trauma to diabetic ketoacidosis and hyperlipidemia, are experienced by dogs, cats, horses, and other veterinary patients throughout the world. Board-certified members of the American and European Colleges of Veterinary Emergency & Critical Care are termed "criticalists" because they provide immediate, essential, and intensive care and management for these animals. In addition to board-certified emergency clinicians working in academia and in private practice, primary care veterinarians also provide emergency medical care at the front line in both specialty and non-specialty veterinary practices. Basic and clinical research in veterinary emergency and critical care medicine that is accessible to all veterinarians is essential to the ongoing advancement and development of the field.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.375
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.001
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 head0.094
GPT teacher head0.443
Teacher spread0.349 · 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
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

Citations7
Published2017
Admission routes1
Has abstractyes

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