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Record W4285220194 · doi:10.5376/mpr.2022.12.0002

SNP Molecular Markers Development and Genetic Diversity Analysis of <i>Forsythia suspensa</i> Based on SLAF-seq Technology

2022· article· en· W4285220194 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

VenueMedicinal Plant Research · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and Biological Activities
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenetic diversityGermplasmSNPSingle-nucleotide polymorphismGeneticsBotanyGenotypeGenePopulationMedicine

Abstract

fetched live from OpenAlex

Forsythia suspensa  (Thunb.) Vahl is an important medicinal plant that has great value to study in China. In this study, the 39  Forsythia suspensa  materials were used specific loci amplified fragment sequencing technology (SLAF-seq) to develop SNP molecular markers. A total of 112.28 Mb reads data were obtained by sequencing. The reads data of each sample ranged from 1 324 860~5 911 565. The average sequencing quality value (Q30) and GC content of samples was 96.29% and 36.97%, respectively. Analysis of bioinformatics, there were 535 357 SLAF tags, in which 262 297 SLAF tags were polymorphic, and the average sequencing depth of the samples was 16.20 x. A total of 1 809 741 SNP molecular markers were obtained and 39  Forsythia suspensa materials were divided into 4 groups. This study could provide theoretical basis for germplasm resource identification and genetic diversity analysis of  Forsythia suspensa .

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 categoriesInsufficient payload (model declined to judge)
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 score0.746
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.263
Teacher spread0.219 · 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