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Investigation of inheritance of glyphosate resistance and the mechanisms of glufosinate resistance in Italian ryegrass (Lolium perenne L. spp. multiflorum (Lam.) Husnot) populations

2011· dissertation· en· W35696881 on OpenAlexfundaboutno aff
Ávila García, W. N. Vidal

Bibliographic record

VenueJournal of Environmental Radioactivity · 2011
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicWeed Control and Herbicide Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMarine Environmental Observation Prediction and Response Network
KeywordsGlyphosateBiologyBackcrossingPopulationResistance (ecology)Mendelian inheritanceGlufosinateLolium perenneLolium rigidumLoliumAgronomyGeneticsBotanyHerbicide resistancePoaceaeGeneMedicine

Abstract

fetched live from OpenAlex

approved: ________________________________________________________ Carol A. Mallory-Smith Italian ryegrass populations have been identified with evolved resistance to glyphosate in orchards with a history of glyphosate use. Two of these populations were selected to investigate the inheritance of glyphosate resistance. The mechanisms involved in the herbicide resistance were an altered target site for the population SF and reduced herbicide translocation for the population OR1. Mendelian inheritance studies and dose response experiments were conducted on the two populations. Four F1 families were formed by reciprocal crosses between each of the glyphosate resistant populations (SF and OR1) and the susceptible population (S) C1. Eight backcross families (BC1) were formed between the F1 individuals from each family and the susceptible population C1. Most of the F1 families resulting from SF and C1 had susceptible:resistant ratios

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 studies0.0000.000
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 head0.017
GPT teacher head0.208
Teacher spread0.191 · 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
Published2011
Admission routes2
Has abstractyes

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