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Record W4315852265 · doi:10.5376/mpb.2022.13.0030

Development and Purity Identification of InDel Marker Based on Re-resequencing of

2022· article· en· W4315852265 on OpenAlexvenueno aff
Riyong Wang, Lingling Xie, Huoqiang Zhou, Yifei Wu, Wei Xiao, Zhuqing Zhang, Baobin Mi

Bibliographic record

VenueMolecular Plant Breeding · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndelGourdBiologyWaxMolecular markerGenomeDNA sequencingGeneticsComputational biologyDNAGeneHorticultureGenotypeSingle-nucleotide polymorphismBiochemistry

Abstract

fetched live from OpenAlex

In order to establish a simple, economic, accurate and reliable method to identify the purity of wax gourd hybrid seeds, an InDel marker characterized by significant differences was developed via whole genome re-sequencing of parent plants of ‘modilong’ wax gourd; Then the developed InDel molecular marker was used to identify the purity of hybrid seeds of ‘modilong’ taking the DNA of its hybrid seeds and parent plants as test DNA, and the obtained results were compared with field identification results. A total of 466 pairs of InDel markers were screened by genome re-resequencing of parent plants of ‘modilong’, and 26 of which with distinct differences were selected to be amplified and both got the strip. Among them, 7 pairs of primers can clearly distinguish the purity of wax gourd samples. The purity of InDel molecular marker identification was more than 99% consistent with the results of field plot planting identification, indicating that the purity results obtained by different methods were highly consistent. The InDel molecular marker screened in this study could be used as the purity identification of wax gourd hybrids.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.283
Teacher spread0.256 · 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 teacher head, 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
Published2022
Admission routes1
Has abstractyes

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