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Record W2142947875 · doi:10.1292/jvms.09-0048

Cerebral Metabolism in Dogs Assessed by 18F-FDG PET: A Pilot Study to Understand Physiological Changes in Behavioral Disorders in Dogs

2010· article· en· W2142947875 on OpenAlexaboutno aff
Mami Irimajiri, Michael A. Miller, Mark A. Green, Christine Jaeger, Andrew U. Luescher, Gary D. Hutchins

Bibliographic record

VenueJournal of Veterinary Medical Science · 2010
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsnot available
FundersSchool of Medicine, Indiana University
KeywordsLabrador RetrieverBreedMedicinePositron emission tomographyStandardized uptake valueInternal medicineNuclear medicinePathologyAnimal scienceBiology

Abstract

fetched live from OpenAlex

The positron emission tomography (PET) imaging technique, which is utilized in human behavior and psychiatric disorder research, was performed on the brains of clinically normal mixed breed dogs, 3 hound-type (long floppy ears) mixed breed dogs and 3 non-hound retriever-type mixed breed dogs. Glucose metabolism was obtained with F-18 fluorodeoxyglucose (FDG), and quantitative analysis was performed by standardized uptake value (SUV) measurement. Magnetic resonance (MR) images were obtained in each dog, and these images were superimposed on PET images to identify anatomical locations. The glucose metabolism in each region of interest was compared between the three hound-type dogs and 3 non-hound-type dogs. The two anatomically different types of dog were compared to assess whether breed-typical behavioral tendencies (e.g., sniffing behavior in hound-type dogs, staring and retrieving in Labrador-type dogs) are reflected in baseline brain metabolic activity. There were no significant differences between the hound-type dogs and non-hound-type dogs in cerebral SUV values. These data might serve as normal canine cerebral metabolism data for FDG PET studies in dogs and form the basis for investigations into behavioral disorders in dogs such as compulsive disorder, anxiety disorders and cognitive dysfunction.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.398
Teacher spread0.333 · 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.

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

Citations16
Published2010
Admission routes1
Has abstractyes

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