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Record W3186403243 · doi:10.1139/cjb-2020-0140

Variations in phytochemistry, morphology, and population structure in <i>Trillium govanianum</i> (Melanthiaceae)

2021· article· en· W3186403243 on OpenAlexvenueno aff
Harsh Kumar Chauhan, David Gallacher, Anil Kumar Bisht, Indra D. Bhatt, Arvind Bhatt, Praveen Dhyani, Pushpa Kewlani

Bibliographic record

VenueBotany · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and Biological Activities
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyIntraspecific competitionEcologyHabitatPopulationMorphology (biology)Arboreal locomotionAdaptation (eye)Threatened speciesBotanyZoology

Abstract

fetched live from OpenAlex

As habitats change, species with higher intraspecific variation have more resources to adapt. Medicinal plants in the Himalayas are increasingly threatened by climate change and other anthropogenic influences. The intraspecific variation within and among 17 populations of the high-elevation herb Trillium govanianum Wall. ex D.Don was studied as an indicator of adaptability. The variation in 19 traits of population structure, morphology, and phytochemistry was assessed across habitats that varied in elevation (2452–3432 m a.s.l.), aspect, latitude (30.1–31.7°N), and arboreal community. The morphology and population structure were conserved among populations but varied among regions. The populations in the lower elevation mixed forests of Tirthan Valley produced smaller rhizomes but larger plant densities, such that plant biomass per square metre was conserved. The phytochemistry varied among regions and populations within regions, indicating significant variation among habitats. The aboveground morphology of the species masks considerable variations in belowground morphology and phytochemistry. The observed variations can help the species to adapt to the changing environmental conditions by provoking a functional response.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.237

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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 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

Citations8
Published2021
Admission routes1
Has abstractyes

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