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Record W4413168403 · doi:10.53555/x0nhag69

Survey And Documentation Of Medicinal Climbers In VTM NSS College Campus, Dhanuvachapuram, Thiruvananthapuram

2023· article· en· W4413168403 on OpenAlexvenueno aff
Dr.Remeshkumar.S Dr.Remeshkumar.S, Dr.Jayalekshmi.R Dr.Jayalekshmi.R, Dr.Biju.C Dr.Biju.C

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDiverse Scientific Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationComputer scienceOperating system

Abstract

fetched live from OpenAlex

Climbing plants are a vital yet often overlooked group of flora that contribute significantly to traditional medicine and biodiversity. This study was undertaken to survey and document the medicinally important climbers present within the campus of VTM NSS College, Dhanuvachapuram, located in the southern part of Thiruvananthapuram district, Kerala. A field survey conducted between January to March 2020 resulted in the identification of 20 species of climbers belonging to 16 genera and 11 families. For each species, the botanical name, family, local name, parts used, and medicinal applications were recorded through field observations, literature review, and informal interviews with local resource persons. The most commonly used plant parts were leaves and roots, and many climbers were traditionally used to treat conditions such as skin diseases, respiratory ailments, digestive issues, fever, and wounds. The dominance of families like Fabaceae, Cucurbitaceae, and Apocynaceae reflects their widespread use in Kerala's folk medicine. The findings underline the importance of conserving medicinal plant resources in educational ecosystems and creating awareness about the medicinal wealth present in our immediate environment.

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)0.038
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.377
GPT teacher head0.466
Teacher spread0.089 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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