MétaCan
Menu
Back to cohort
Record W3081063810 · doi:10.1139/gen-2020-0050

Molecular confirmation of varietal status in bottle gourd (<i>Lagenaria siceraria</i>) using genotyping-by-sequencing

2020· article· en· W3081063810 on OpenAlexvenueno aff
Jacky Amenan Konan, Romain Guyot, Kouamé Kevin Koffi, I. Vroh‐Bi, Arsène Irié Bi Zoro

Bibliographic record

VenueGenome · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvances in Cucurbitaceae Research
Canadian institutionsnot available
Fundersnot available
KeywordsLagenariaBottle gourdBiologyGourdSingle-nucleotide polymorphismGenotypingSubspeciesBotanyGeneticsGenotypeHorticultureGeneZoology

Abstract

fetched live from OpenAlex

subspecies are sufficiently different to be considered as varieties, but they are assigned into different taxonomic ranks. Genotyping-by-sequencing (GBS) of 95 different accessions from the Nangui Abrogoua University collection was used to confirm the varietal status in bottle gourd. This analysis produced 22 575 single-nucleotide polymorphisms (SNPs). Cluster analyses conducted with 2250 (9.96%) SNPs distinctly separated hard-shelled from soft-shelled types. Analysis of 23 SNPs located in 11 genes coding for traits that differentiate the two types of gourds revealed that genes in the soft-shelled types had about 21% fewer SNPs than genes within hard-shelled gourds, but the latter had more non-synonymous SNPs. Cluster analyses conducted with the 23 SNPs fitted well with the structure defined by the 2250 SNPs, suggesting the implication of these SNPs in the varietal differentiation of bottle gourd. These nucleotide changes along with the genetic relationships between the accessions provide molecular proof supporting the status of two varieties. To prevent the confusion inherent in the use of synonyms and homonyms in bottle gourd, we suggest the terms hard-shelled and soft-shelled to designate, respectively, the varieties used as utensils and those grown for their edible seeds.

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)0.000
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 score0.056
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.025
GPT teacher head0.290
Teacher spread0.264 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueGenomeSame topicAdvances in Cucurbitaceae ResearchFrench-language works237,207