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Record W2083023111 · doi:10.1024/0036-7281.151.11.521

Welpenfütterung in der Schweiz

2009· article· de· W2083023111 on OpenAlexaboutno aff
Annette Liesegang, Carmen Füglistaller, Brigitta Wichert

Bibliographic record

VenueSchweizer Archiv für Tierheilkunde · 2009
Typearticle
Languagede
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsPuppyBreedBeagleAnimal husbandryBody weightVeterinary medicineBiologyAnimal scienceMedicineEcology

Abstract

fetched live from OpenAlex

In this study breeders and owners of 8 different dog breeds (Beagle, Bernese Mountain Dog, Cavalier King Charles Spaniel, Great Dane, German Shepherd (GS), Labrador, Papillon, Sheltie) were interviewed to obtain information on puppy feeding in Switzerland. Besides answering a questionnaire (husbandry and feeding of the puppies), the participation in this study included weekly weighing of the animals as well as exact documentation of the amount fed to the animals. Totally 67 dog breeders and 131 new owners of puppies participated. The weight development of the puppies was mostly parallel to the growth curve in the GS, Labradors and Shelties. There were some substantial differences to the ideal growth curve within the other breeds. The daily mean energy requirement was estimated too high, when including the growth curves. 80 - 90 % of the recommendations would be sufficient for most animals. The calcium supply was in the range of tolerance in all breeds. Nearly all breeders used commercially available complete food while raising the puppies. No breed-specific differences could be shown.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.035
GPT teacher head0.337
Teacher spread0.302 · 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
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

Citations2
Published2009
Admission routes1
Has abstractyes

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Same venueSchweizer Archiv für TierheilkundeSame topicVeterinary Orthopedics and NeurologyFrench-language works237,207