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Record W4386430074 · doi:10.5376/ijmz.2023.13.0001

Exploring the Categories and Main Morphological Features of Cats

2023· article· en· W4386430074 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Molecular Zoology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCATSBreedStyle (visual arts)DomesticationAncestorPsychologyGeographyBiologyMedicineEcologyArchaeology

Abstract

fetched live from OpenAlex

Cats are a beloved pet animal and widely exist in human society. Their unique appearance and behavioral characteristics are highly praised by people. This article will focus on discussing the main features and classifications of cats, including their physical features such as body size, hair color and texture, shape and size of eyes and ears, and shape and length of tails; the behavioral characteristics of cats, such as activity time and style, social behavior, hunting skills, and sleep habits;  a nd classify cats according to different classification methods such as breed, ancestor, and geographical distribution. Through literature review and empirical research, this article aims to deeply explore the scientific principles and cultural background behind the characteristics and classification of cats, providing a deeper understanding and understanding of cats as an important component of human culture and society. The research results are of great significance for deepening people's understanding of cats, promoting the development of pet culture, and promoting relevant scientific research.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.232

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 head0.048
GPT teacher head0.346
Teacher spread0.298 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

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