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Random amplified polymorphic DNA variation within and among meadow bromegrass progeny types

2003· article· en· W2036094564 on OpenAlexaff
M. R. A. de Araújo, Bruce Coulman, Daryl J. Somers, Yasas S. N. Ferdinandez, G. Rakow

Bibliographic record

VenuePlant Breeding · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicTurfgrass Adaptation and Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyGenotypeGenetic variationGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Ten meadow bromegrass genotypes tested as half‐sib (polycross, PX; open‐pollinated, OP) and selfed (S1) progenies were surveyed using random amplified polymorphic DNA. Fourteen primers, which produced 32 markers, were selected to determine the genotypes of 360 individuals from the three progeny tests. Analysis of molecular variance was performed in each progeny test, and genetic distances between genotypes and progeny types were determined. Among genotype genetic variation in half‐sib (PX and OP) progenies was similar. Genetic variation among genotypes for S1 progenies (30.5%) was about twice that found in the half‐sib progenies. Variation between individual S1 progenies ranged from 15.7% to 50.1%, while in the half‐sib progenies, the range was 6.9‐24.1%. Based on average distances between progeny types for a given genotype, OP and PX were closer to each other than to the S1. An analysis of variance of the molecular marker frequency occurrence was performed for 12 plants within each progeny type of each genotype. Marker frequencies, expressed in percentages, ranged from 10.7% to 84.3%. No significant differences were found for genotype and progeny type‐genotype interaction suggesting that all genotypes behave in a similar manner across the different progeny types.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.190
Teacher spread0.173 · 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 designBench or experimental
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

Citations1
Published2003
Admission routes1
Has abstractyes

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