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Record W4382301995 · doi:10.5376/bm.2023.14.0002

Optimization of ISSR-PCR Reaction System in <i>Pinellia ternata</i>

2023· article· en· W4382301995 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.

venuePublished in a venue whose home country is Canada.
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

VenueBioscience Methods · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsnot available
Fundersnot available
KeywordsPinellia ternataPrimer (cosmetics)Molecular biologygenomic DNAPolymerase chain reactionDNABiologyChemistryGeneticsMedicineGene

Abstract

fetched live from OpenAlex

In order to establish and perfect ISSR-PCR reaction system of Pinellia ternata , we used P. ternata  from Sichuan region as the test material in this research. Genomic DNA of whole plant of P. ternata  was used as template, UBC818 primer was used in ISSR-PCR system, L 16 (4 5 ) orthogonal test and single factor experiment were used to optimize the system. Based on the visual analysis of orthogonal experiment, we found the following are the influences of various factors on the experimental results in turn: dNTPs, primer, Mg 2+, Taq  DNA polymerase, DNA template. Based on single factor screening test, we found the best ISSR-PCR reaction system. The total reaction volume is 20.0 μL, containing dNTPs 0.2 mmol/L, primer 0.8 μmol/L, Mg 2+ 2.0 mmol/L, Taq  DNA polymerase 0.075 U/μL, DNA 15 ng, annealing temperature 56℃. In this study, ISSR-PCR reaction system was optimized which will be applied to detect the genetic stability of P . ternata  tissue culture seedlings.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.039
GPT teacher head0.294
Teacher spread0.255 · 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