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Influencia de las fases lunares como una herramienta de medición de acontecimientos reproductivos. Primera aproximación

2019· article· es· W3036543900 on OpenAlexaboutno aff
Edgar Lenin Aguirre Riofrío, Melania de Lourdes Uchuari-Pauta, Jaime Ureña-Ureña, Carlos Rosillo-Cueva

Bibliographic record

VenueJournal of the Selva Andina Animal Science · 2019
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Full moonMatingHerdSeasonal breederGeographyAnimal scienceBiologyEcologyArchaeology

Abstract

fetched live from OpenAlex

There is a proven influence of the moon on some agricultural tasks, but at level of the animáis such influence has been little analyzed. The objective of this research was the analyze of influence moon about some reproductive process in bovines. The results of the present investigation were obtained by X2 from a data set of 830 registrations of natural heat and 305 data of births, collected of some herds located in the Southern Región of Ecuador-South America. The study showed that the natural heat and the births in bovines follow a eyelieal process, having a higher incidence of these processes in the phases of first quarter and full moon, while in the waning phase, the incidence is lower. Also is noted that the mating cows in any phase, tend to calve in the two following phases and the probability of parturition in the same phase that oceurred the mating is lower. As for the synchronization of heat, the better results in the conception rate at the first service were obtained when the female bovine were synchronizing in the dark moon and first quarter phases. In conclusión have influence of the moon phases in the reproductive process analyzed, so is important it's considered for take better results.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.639
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.280
Teacher spread0.265 · 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 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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

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