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Record W6969278141 · doi:10.5683/sp3/ytihqi

The genetic architecture of flowering time and related traits in two early flowering maize lines 2007 [Canada]: Bioinformatics and quantitative genetics

2013· dataset· en· W6969278141 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2013
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInbred strainInbreedingGenetic architectureQuantitative trait locusPopulationGenetic analysisQuantitative geneticsGenetic variabilityGenetic linkage

Abstract

fetched live from OpenAlex

Flowering time is the major factor in determining maize (Zea mays L.) maturities. Genetic bases of flowering time and other agronomically important traits were examined in a set of interheterotic-pattern recombinant inbred lines (RILs). The RILs were developed from crossing the short-season Iodent inbred line CG60 with the short-season Stiff Stalk inbred line CG102. Recombinant inbred lines were derived through single-seed descent (S-RILs) or intermated for three generations before inbreeding (I-RILs), thereby increasing recombination. In this study the genetic means, covariances, and variances of flowering time (days to anthesis, DA, and days to silking, DS) and a number of flowering-time-associated traits, leaf number (LN), plant height (PH), and stay green (SG), in a set of short-season, interheterotic-pattern recombinant inbred lines (RILs) representing two levels of intermating were examined. The objectives were: (1) to evaluate the genetic basis of DA, DS, LN, PH, SG, and canopy reflectance traits within the short-season parental lines, (2) to evaluate genetic and phenotypic correlations between DA, DS, LN, PH, SG, and canopy refl ectance traits, and (3) to evaluate whether disruption of putative coupling and repulsion phase linkage blocks causes changes in population means, genetic variances, and genetic correlations.

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: Dataset · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.173

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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
GenreDataset

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
Published2013
Admission routes2
Has abstractyes

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