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Record W2892004284 · doi:10.1101/412874

Assessment of genetic structure of the endangered forest species <i>Boswellia serrata</i> Roxb. population in central india

2018· preprint· en· W2892004284 on OpenAlexfundno aff
Vivek Vaishnav, Shashank Mahesh, Pramod Kumar

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldMedicine
TopicPharmacological Effects of Medicinal Plants
Canadian institutionsnot available
FundersIndian Council of Forestry Research and EducationTerry Fox Research Institute
KeywordsGenetic diversityBiologyIn situ conservationEx situ conservationEndangered speciesBoswellia serrataPopulationGenetic variationGene flowBurseraceaeGenetic structureEcologyEvolutionary biologyHabitatGeneticsGene

Abstract

fetched live from OpenAlex

ABSTRACT Boswellia serrata Roxb., a commercially important species for its pulp and pharmaceutical properties was sampled from three locations representing its natural distribution in central India for genetic characterization through 56 RAPD + 42 ISSR loci. The wood fiber dimensions measured for morphometric characterization confirmed 11.36% of the variation in the length and 8.75% of the variation in the width indicating its fitness for local adaptation. Bayesian and non-Bayesian approach based diversity measures resulted moderate within population gene diversity (0.26±0.17), Shannon’s information index (0.40±0.22) and panmictic heterozygosity (0.28±0.01). A high estimate for genetic differentiation measures i.e. G ST (0.31), G ST -B (0.33±0.02) and θ-II (0.45) led to the distinct clusters of the sampled genotypes representing their regional variability due to limited gene flow and total absence of natural regeneration. We report the first investigation of the species for its molecular characterization emphasizing the urgent need for the genetic improvement program for the In-situ / Ex-situ conservation and sustainable commercialization.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.262
Teacher spread0.247 · 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.

Study designObservational
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

Citations1
Published2018
Admission routes1
Has abstractyes

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