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Record W2080639991 · doi:10.1212/wnl.62.12.2303

Seizure-alerting and -response behaviors in dogs living with epileptic children

2004· article· en· W2080639991 on OpenAlexaff
Adam Kirton, Elaine Wirrell, James Zhang, Lorie Hamiwka

Bibliographic record

VenueNeurology · 2004
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsAnticipation (artificial intelligence)PsychologyEpilepsyAudiologyDevelopmental psychologyMedicinePediatricsNeuroscience

Abstract

fetched live from OpenAlex

There is little evidence for the ability of dogs to anticipate human seizures. Families of epileptic children were surveyed to investigate seizure-related behaviors in dogs. Approximately 40% of families owned a dog, about 40% of these had seizure-specific behavior, and about 40% of these (approximately 15% overall) showed anticipatory ability. Anticipation occurred early and was both sensitive and specific. Quality of life was higher in families with a dog that responded to seizures.

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 score0.005
Threshold uncertainty score0.334

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 head0.009
GPT teacher head0.271
Teacher spread0.261 · 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

Citations62
Published2004
Admission routes1
Has abstractyes

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