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Influencia de factores ambientales y antrópicos en la población de ostión Crassostrea virginica (Bivalvia: Ostreidae), en río Cauto, Cuba

2020· article· es· W3007090208 on OpenAlexaff
Abel Betanzos-Vega, Gustavo Arencibia-Carballo, Hever Latisnere‐Barragán, José Manuel Mazón‐Suástegui

Bibliographic record

VenueRevista Mexicana de Biodiversidad · 2020
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicSoil Science and Environmental Management
Canadian institutionsCanadian Bank Note Company (Canada)
Fundersnot available
KeywordsGeographyBiology

Abstract

fetched live from OpenAlex

En Cuba, el ostión de fondo (OF) Crassostrea virginica (Gmelin, 1791) aportó durante 2008-2013 más de 30% a la captura nacional de ostiones del género Crassostrea. De una biomasa inicial no explotada (≥ 1,500 t), la población delrío Cauto se redujo a 277 t en 2014. El objetivo del presente estudio fue determinar los principales factores naturales y antrópicos que han afectado la calidad del hábitat y disminuido la población de C. virginica en el río Cauto. Seobtuvieron datos hidrológicos y biológicos poblacionales antes y después de un derrame accidental de aguas residuales de una industria azucarera de la región, que aunada a precipitaciones abundantes y aportes terrígenos fluviales, afectódrásticamente la calidad del agua registrándose valores de turbidez (> 8 FTU), oxígeno disuelto (< 3 mgO2 L-1), demanda química de oxígeno (DQO, > 11 mgO2 L-1) y salinidad (< 10 UPS), que redujeron la sobrevivencia (< 40%)y la abundancia del OF (< 30 ostiones/m2). Se identificaron factores naturales y antrópicos que afectan al hábitat y a la población ostrícola. Se proponen valores de referencia indicadores de buena calidad fisicoquímica del agua ensitios donde existan bancos naturales de C. virginica o se pretenda realizar su cultivo.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.998

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.229
Teacher spread0.216 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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