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Record W2527945835 · doi:10.1007/s13205-016-0534-3

Progress in genome sequencing will accelerate molecular breeding in cotton (Gossypium spp.)

2016· review· en· W2527945835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venue3 Biotech · 2016
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicResearch in Cotton Cultivation
Canadian institutionsnot available
FundersInstitute of GeneticsMinistry of Agriculture of the People's Republic of ChinaInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesChinese Academy of Sciences
KeywordsGenomeBiologyMolecular breedingComputational biologyBiotechnologyGossypiumWhole genome sequencingGeneticsGene

Abstract

fetched live from OpenAlex

Cotton (Gossypium spp.) is the single most important spinning fiber that has economic significance worldwide. Cotton is one of the most value-added crops and an excellent model system for the analysis of polyploidization and cell development. Thus, the Cotton Genome Consortium has made rapid and significant progress in whole genome sequencing studies in the last decade. Developments in cotton genome sequencing and assembly provide powerful tools for dissecting the genetic and molecular bases of agronomically important traits and establishing regulatory networks on these processes, which leads to molecular breeding. Here, we briefly review these advances, emphasizing their implications in the genetic improvement of cotton with a particular focus on fiber quality and yield. Moreover, major progresses in chloroplast and mitochondrial genomes have also been summarized.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.102
GPT teacher head0.343
Teacher spread0.240 · 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