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Record W3171771190 · doi:10.56093/ijas.v90i8.105948

Exploring the genetic variability of citrus butterfly (Papilio demoleus) using DNA barcode

2020· article· en· W3171771190 on OpenAlexaboutno aff
Vikas Jindal

Bibliographic record

VenueThe Indian Journal of Agricultural Sciences · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsnot available
FundersScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsPhylogenetic treeBiologyDNA barcodingGenetic diversityGenetic variationGenetic divergenceEvolutionary biologyGeneGeneticsVeterinary medicineZoologyPopulation

Abstract

fetched live from OpenAlex

The present study is first and initial report from India on developing barcodes and molecular identification of citrus swallow tail butterfly (Papilio demoleus L.) based on mtCOI region and species composition from Abohar, Jalandhar, Ludhiana, Sangrur areas of Punjab on citrus host plants. The corresponding genomic DNA isolation, PCR amplification, detectable genetic divergence, molecular identification and phylogenetic tree were assessed. Using the specific set of primers the samples yielded specific fragment of 658 bp. The amplified PCR product was sequenced and identified as Papilio demoleus and submitted to BOLD database. The 658 bp mtCOI gene sequences from Abohar, Ludhiana, Jalandhar were 100% similar however the sequence from Sangrur region show mutations at three different positions showing a variation of 0.45% from rest of the populations of Punjab. The phylogenetic tree was developed and it was revealed that all the populations of Punjab are in same cluster and when compared with populations from other countries, it form two main clusters which are different from each other by 3.70%. The cluster one includes all the populations of Australia, India, USA and Pakistan and the cluster two include totally different populations from Canada. In cluster one the populations from Australia and USA forms one subgroup while populations from India and Pakistan form second subgroup.

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)0.001
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 score0.427
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.062
GPT teacher head0.239
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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