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Record W3157550810 · doi:10.22215/etd/2020-14255

A functional genomics approach in identifying the underlying gene for the E8 maturity locus in soybean (Glycine max)

2020· dissertation· en· W3157550810 on OpenAlexaffabout
Michael I. Sadowski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsCarleton University
Fundersnot available
KeywordsLocus (genetics)BiologyFunctional genomicsGenomicsGeneMaturity (psychological)GeneticsQuantitative trait locusGenomeCropComputational biologyBiotechnologyAgronomyPsychology

Abstract

fetched live from OpenAlex

Soybean is an economically important crop that has rapidly expanded throughout Western Canada and Northern regions.To continue this expansion, understanding the time of flowering and maturity pathway is an important factor for soybean adaptation.So far, eleven maturity loci have been identified for this pathway, however the underlying gene for one third of them remain unknown.The E8 maturity locus was previously identified in our lab on chromosome 4 using classical breeding practices and genome wide SSR marker analysis.A bioinformatics approach utilizing PIPE (Protein-protein Interaction Prediction Engine) along with a plethora of functional genomics resources and prediction tools has short listed this region down to 3 promising candidates; Glyma.04G124600,Glyma.04G140000, and Glyma.04G101500,all involved in light perception.Further analysis of these candidates will reveal the underlying gene for E8 and shed light on the flowering mechanism in the important food crop soybean.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.089
GPT teacher head0.267
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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Same topicSoybean genetics and cultivationFrench-language works237,207