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Los marcadores microsatélite revelan la reestructuración genética de Medicago sinskiae (Fabaceae) en el oeste y el sudoeste de Irán

2022· article· es· W4225575029 on OpenAlexaff
Raha Zareei, Ernest Small, Mostafa Assadi, Iraj Mehregan

Bibliographic record

VenueCollectanea Botanica · 2022
Typearticle
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsHumanitiesFabaceaeForestryBiologyGeographyPhysicsBotanyArt

Abstract

fetched live from OpenAlex

Medicago sinskiae es considerada una especie rara en la flora iraní con únicamente unas pocas citas en las tres últimas décadas. Se han muestreado ocho poblaciones (62 individuos) de M. sinskiae, una población de M. rigidula (siete individuos) y una población de M. constricta (cinco individuos) en el oeste y el suroeste de Irán que han sido analizadas con marcadores microsatélite. Se han utilizado nuevos primers obtenidos con tecnología NGS. Los análisis de PCoA, Clustering y Structure no muestran un patrón geográfico para los clústeres genéticos. Los resultados muestran que M. sinskiae es principalmente una especie autógama. Se asume que los altos niveles de flujo genético (Nm) y la homogeneidad genética poblacional están afectados por una rápida dispersión y un flujo genético no localizado. Recolecciones extensivas realizadas recientemente en el oeste y el suroeste de Iran muestran que el rango de distribución esta especie se está incrementando. Finalmente, nuestros resultados indican que M. sinskiae está diferenciada de las especies M. rigidula y M. constricta en Irán.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.257
Teacher spread0.252 · 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
Published2022
Admission routes1
Has abstractyes

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