MétaCan
Menu
Back to cohort
Record W2591547627 · doi:10.7482/0003-9438-57-028

Generalized procrustes analysis (GPA) as a tool to discriminate among sheep breeds

2014· article· en· W2591547627 on OpenAlexaff
Isabel Moreno‐Indias, A. Horcada, A. Molina, M. Juárez

Bibliographic record

VenueArchives animal breeding/Archiv für Tierzucht · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsAgriculture and Agri-Food Canada
FundersInstituto de Salud Carlos IIIInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria
KeywordsBreedBiologyAnimal scienceSensory analysisZoologyFood science

Abstract

fetched live from OpenAlex

Abstract. Forty male lambs of five Southern Spanish breeds were used to study the effects of the breed in their sensorial characteristics. The used breeds were: Segureña, Spanish Merino, Grazalema Merino, Churra Lebrijana and Montesina breeds. Milk lambs were slaughtered at 12 kg of live weight. A descriptive sensory evaluation was developed using the longissimus lumborum from each animal by a panel of 12 experts and a Generalized Procrustes Analysis (GPA) was used to discriminate among them. Generalized Procrustes Analysis clearly differentiated Churra Lebrijana of out the rest breeds. Churra Lebrijana was defined as more tender, juicier and with less lamb odour than the rest of the Southern Spanish lamb breeds. Thus, GPA is able to discriminate among breeds.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.024
GPT teacher head0.262
Teacher spread0.238 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueArchives animal breeding/Archiv für TierzuchtSame topicMeat and Animal Product QualityFrench-language works237,207