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Record W2382807106

RAPD Analysis of Castor Seed Size Traits Linkage

2015· article· en· W2382807106 on OpenAlexaff
Bao Chun-guan

Bibliographic record

VenueActa Agriculturae Boreali-Sinica · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPeanut Plant Research Studies
Canadian institutionsScience North
Fundersnot available
KeywordsRAPDRicinusBiologyGenome sizePrimer (cosmetics)DNAGenomeBiotechnologyBotanyGeneticsGeneChemistryGenetic diversityPopulation
DOInot available

Abstract

fetched live from OpenAlex

Castor seed size varies greatly due to breed,has yet to see molecular biology research on castor bean size traits associated with the development. In this experiment,32 castor seeds of different sizes as research material,with U25( 55) uniform design for seed size traits RAPD-PCR reaction system and conditions were optimized. The optimal reaction system: 25 μL system,10 × Buffer 2. 7 μL,d NTP 2. 4 μL,Mg2 +2. 4 μL,DNA 1. 7 μL,primers 1. 9μL,Taq polymerase 2. 0 μL,dd H2 O 11. 9 μL. The best reaction conditions were: 94 ℃ 150 s; 94 ℃ 45 s,39 ℃65 s,72 ℃ 90 s,35 cycles; 72 ℃ 10 min; 4 ℃ preservation. With SB-002 primer( nucleotide sequence( 5'-3') :TGCCGAGCTG),using the best reaction system and conditions,screening a different band in the largest grain castor seeds,sequencing results were compared in the NCBI found with high yield rice genome DNA,mRNA or c DNA homology of 100%. Therefore,It can be concluded that the different band relevant to castor seed yield,laid the foundation for the relevant molecular mechanisms of castor seed size traits studied.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0020.001

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 head0.049
GPT teacher head0.267
Teacher spread0.218 · 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
Published2015
Admission routes1
Has abstractyes

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