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Record W3152594877

Comportamiento estacional de la leptospirosis en equinos durante un decenio en Camagüey

2019· article· es· W3152594877 on OpenAlexaboutno aff
Herlinda de la Caridad Rodríguez Torrens, Guillermo Barreto Argilagos, Tatiana García Casas, Roberto Vázquez Montes de

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languagees
FieldImmunology and Microbiology
TopicLeptospirosis research and findings
Canadian institutionsnot available
Fundersnot available
KeywordsLeptospirosisSeasonalityLeptospiraVeterinary medicineZoonosisQuarter (Canadian coin)GeographyBiologyAnimal scienceEcologyMedicineArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Antecedentes: La leptospirosis es la zoonosis más extendida en la actualidad. Numerosas especies animales actúan como reservorios de la espiroqueta. Esta investigación tuvo como objetivo establecer su comportamiento estacional en equinos. Métodos: Para ello se utilizó la información relativa a 1 099 sueros equinos reactores a Leptospira colectados mensualmente durante 10 años. Se realizó una descomposición estacional por el método multiplicativo, con el cual se estableció la estacionalidad con periodicidad trimestral de la proporción de reactores positivos durante el decenio. Resultados: La mayor proporción de reactores correspondió al trimestre octubre, noviembre y diciembre, con un factor estacional por encima del 100 %. Coincidente con período poco lluvioso, resultado que no se corresponde con la mayoría de lo referido para humanos y otras especies animales. Conclusiones: La mayor proporción de equinos reactores a Leptospira correspondió con el trimestre cuarto del decenio estudiado; período poco lluvioso, lo cual difiere de gran parte de lo publicado, por lo que es preciso abundar más al respecto.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.084
GPT teacher head0.517
Teacher spread0.433 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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