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Record W2110177454 · doi:10.2460/javma.2002.220.1315

Effects of diet restriction on life span and age-related changes in dogs

2002· article· en· W2110177454 on OpenAlexaboutno aff
Richard D. Kealy, Dennis F. Lawler, J.M. Ballam, Sandra L. Mantz, Darryl N. Biery, Elizabeth H. Greeley, George Lust, Mariangela Segre, Gail K. Smith, Howard D. Stowe

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2002
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLife spanDiseaseClinical significancePhysiologyInternal medicineGerontology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the effects of 25% diet restriction on life span of dogs and on markers of aging. DESIGN: Paired feeding study. ANIMALS: 48 Labrador Retrievers. PROCEDURES: Dogs were paired, and 1 dog in each pair was fed 25% less food than its pair-mate from 8 weeks of age until death. Serum biochemical analyses were performed, body condition was scored, and body composition was measured annually until 12 years of age. Age at onset of chronic disease and median (age when 50% of the dogs were deceased) and maximum (age when 90% of the dogs were deceased) life spans were evaluated. RESULTS: Compared with control dogs, food-restricted dogs weighed less and had lower body fat content and lower serum triglycerides, triiodothyronine, insulin, and glucose concentrations. Median life span was significantly longer for dogs in which food was restricted. The onset of clinical signs of chronic disease generally was delayed for food-restricted dogs. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that 25% restriction in food intake increased median life span and delayed the onset of signs of chronic disease in these dogs.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.039
GPT teacher head0.299
Teacher spread0.260 · 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 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

Citations615
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Veterinary Medical AssociationSame topicVeterinary Medicine and SurgeryFrench-language works237,207