MétaCan
Menu
Back to cohort
Record W3121159613 · doi:10.5376/jtsr.2020.10.0002

Analysis of DNA Barcoding Suitable for Tea Tree Field Genebank

2020· article· en· W3121159613 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

VenueJournal of Tea Science Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsnot available
Fundersnot available
KeywordsDNA barcodingBiologyChloroplast DNADNA sequencingHaplotypeTree (set theory)BotanySequence (biology)GenePhylogenetic treeEvolutionary biologyGeneticsGenotypeMathematicsCombinatorics

Abstract

fetched live from OpenAlex

With the development of research for DNA barcoding, its application has attracted more and more attention. In this study, 100 tea tree samples were selected as subjects, the partial sequences of chloroplast  matK  and  rbcL  genes were used to investigate the molecular barcodes suitable for tea tree The results showed that the  rbcL  sequences of 100 tea samples were identical, the  matK  sequences were different, the genetic distance ranged from 0.000 to 0.032, the sequences could be divided into 14 haplotypes, Hd and Pi were 0.604 and 0.23×10-2, at the same time, the construction analysis of the sequence is carried out. The results showed that the  matK sequence could be used in the development and utilization of DNA barcoding of tea tree field genebank.

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)0.003
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 score0.016
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.154
GPT teacher head0.440
Teacher spread0.286 · 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