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Record W2531902778 · doi:10.5539/jas.v8n11p51

Genetic Divergence among Camu-Camu Plant Populations Based on the Initial Characteristics of the Plants

2016· article· en· W2531902778 on OpenAlexvenueno aff
Edvan Alves Chagas, Oscar José Smiderle, Abanto-Rodriguez Carlos, Pollyana Cardoso Chagas, Adamor Barbosa Mota Filho, Olisson Mesquita Souza, A. C. C. Cordeiro

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGrowth and nutrition in plants
Canadian institutionsnot available
Fundersnot available
KeywordsSeedlingMahalanobis distanceGenetic divergenceBiologyHorticultureDivergence (linguistics)GerminationGenetic diversitySowingGenetic distanceBotanyGenetic variationMathematicsPopulationStatisticsGeneticsDemography

Abstract

fetched live from OpenAlex

<p>The objective in the present work was to evaluate the genetic diversity among 15 indigenous populations of camu-camu plants, identifying important characteristics in the evaluation of genetic divergence, based on the initial characteristics of the seedlings. Seeds extracted from fruits deriving from fifteen indigenous populations of camu-camu were collected. The experimental design was entirely random, with fifteen treatments (populations), and fifteen repetitions (each sub-sample), considering 30 seeds per subsample as an experimental unit. At 40 days after sowing the following were evaluated: the percentage of emergence, the index of emergence velocity, the average time of germination, the height of the seedling and the number of leaves. The data obtained was submitted to variance analysis, and the averages were grouped by the Scott and Knott (1974) test. The genetic diversity was studied according to the Tocher grouping method, based on the Mahalanobis distance (D<sup>2</sup><sub>ii</sub>) and canonical variables. The fifteen populations are divergent among themselves and the Rio Branco Estirão do Veado, Rio Branco Onofre and Igarapé Agua Boa populations are indicated to have hybridization with other populations due to the high divergence, as well as the rates of emergence and vigor of the seedlings. The height of the seedlings, percentage and speed of emergence, are those that most indicate genetic divergence. The measuring techniques of genetic divergence, canonical variables Mahalanobis distances are useful and corroborating in the evaluation of genetic divergence of the camu-camu plant.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.289
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.223
Teacher spread0.189 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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