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Record W3117690781 · doi:10.52904/0718-4646.2015.441

Estrategias de selección de progenies de Eucalyptus urophylla S. T. Blake en la Región de Selvíria - Barsil

2015· article· es· W3117690781 on OpenAlexaff
M. A. P. Moraes, Silvelise Pupin, Christiane Silva Souza, A. C. Miranda, Paulo Henrique Müller da Silva, J.L.S Sasaki, Mário Luiz Teixeira de Moraes

Bibliographic record

VenueCiencia & Investigación Forestal · 2015
Typearticle
Languagees
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsBiologyHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La forma en que los individuos son seleccionados en una prueba de progenie es fundamental en la conservación y mejoramiento genético. Una prueba de progenie con un total de 26 progenies de Eucalyptus urophylla, proveniente de Río Claro-SP, con selección en Anhembi-SP, se instaló en Selvíria-MS el 03/10/1991, con un espaciamiento de 3,0 x 3,0 m, seis plantas por parcela lineales y cuatro repeticiones, en bloques al azar. . El suelo es un Latosol Rojo distrófico, la precipitación anual del lugar es de 1.300 mm y la temperatura media anual es de 25º C. A los 19 años de edad se evaluó lo carácter DAP (diametro a la altura del pecho) por el procedimiento REML/BLUP, y presentó una media de 27,4 cm.. Con base en este carácter, se utilizaron dos estrategias de selección: La primera consideró la selección de los primeros 104 mejores individuos independientemente de la progenie a la cual pertenecían, seleccionados por su valor genético dado por BLUP. Esta selección proporciona un tamaño efectivo de 33 y una ganancia en la selección de 3,1%. En la segunda estrategia se optó por la selección solo dentro de las progenies; los cuatro mejores individuos de cada progenie, lo que proporciona un tamaño efectivo de 59 y una ganancia de 1,8%

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.242
Teacher spread0.229 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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