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Record W4411617946 · doi:10.51847/nqthk3vz8m

10.51847/NQThk3Vz8m

2000· article· en· W4411617946 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKhyber pakhtunkhwaMedicineToxicologyBiologySocioeconomicsSociology

Abstract

fetched live from OpenAlex

The present study was conducted to evaluate the ethno-veterinary medicinal plants traditionally used for curing of animals in district Charsadda.Farmers in most of the villages in District Charsadda treat the animals using local plants and because of poverty, they do not depend on English medicines.Survey was carried out and information was collected from local peoples that most of them were formers.Questionnaires were asked from 40 informants of various villages.A total of 60 plants belonging from total 34 families were collected from district that local people use for Ethnoveterinary purpose (EVP).Most commonly used parts of ethnoveterinary plants are Fruits 14 (8.4%), leaf and seeds 12 (7.2%),Whole plant 6 (3.6%), bark 4 (2.4%),Rhizome 3 (1.8%),Flower, bulb, oil and latex 2 each of one is (1.2%) and stem are 1 (1.6%).It was also observed that old people from age of 75-80 have most knowledge about the ethnoveterinary plants.Solanaceae is the highest family in the study area involved in curing of different ethnoveterinary medicines' preparations.It was also observed that skin diseases are common in the area followed by weakness, diarrhea, shortage of milk and death during birth is very rare in District Charsadda.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.974
Threshold uncertainty score0.114

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)0.9870.942

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 head0.013
GPT teacher head0.183
Teacher spread0.170 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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