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Record W2102289933 · doi:10.1136/vr.161.11.375

Review of pathophysiology and clinical management of narcolepsy in dogs

2007· review· en· W2102289933 on OpenAlexaboutno aff
M. Tonokura, Kanna Fujita, Seiji Nishino

Bibliographic record

VenueVeterinary Record · 2007
Typereview
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsNarcolepsyCataplexyOrexinEtiologyMedicineNeurologySleep paralysisNeurosciencePsychologyPathologyInternal medicineReceptorPsychiatryNeuropeptide

Abstract

fetched live from OpenAlex

Narcolepsy is a chronic sleep disorder that affects human beings and animals. Up to 17 breeds of dogs are affected sporadically, and familial forms occur in dobermanns, labrador retrievers and dachshunds. These dogs display characteristics strikingly similar to those of human narcolepsy, including cataplexy (a sudden loss of muscle tone in response to emotional stimulation) and a shorter sleep latency. It has recently been shown that the aetiology of both the familial form (receptor null mutation) and the sporadic form (loss of ligand production) of canine narcolepsy is associated with a deficit in hypocretin/orexin neurotransmission. Hypocretin deficiency can be detected by the measurement of hypocretin-1 in cerebrospinal fluid, and this could be used to diagnose hypocretin ligand deficient cases in clinical practice. Narcolepsy is neither progressive nor life-threatening, but the clinical signs persist throughout life, and lifelong treatment and care are required. This article reviews the recent progress in narcolepsy research in dogs, and describes the diagnosis and treatment of the disease.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.320
GPT teacher head0.502
Teacher spread0.182 · 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 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

Citations33
Published2007
Admission routes1
Has abstractyes

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