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Record W3195127693 · doi:10.21065/19257430.1.2

MEDICINAL PLANTS USED BY TRADITIONAL HEALERS OF PUNJAB, PAKISTAN

2013· article· en· W3195127693 on OpenAlexvenueno aff
Sinia Imtiaz, Sahar Abdullah, Saima Afzal, Gohar Rehman, Mamoona Waheed

Bibliographic record

VenueCanadian Journal of Applied Sciences · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEthnobotanical and Medicinal Plants Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousMedicinal plantsTraditional medicineTraditional knowledgeEthnobotanyEthnomedicineSyzygiumGeographyAsteraceaeBiologyBotanyMedicineEcology

Abstract

fetched live from OpenAlex

This study is aimed to document the indigenous knowledge of medicinal plants used by traditional healers of Punjab, Pakistan. The medicinal uses were documented by semi structured interview of the registered herbalists & relevant literatures were also reviewed. The data was collected by visiting the study area from Feb 2013 to August 2013. All traditional plants having therapeutic activity were crosschecked with existing literature on ethno botany. In our data about 150 indigenous plant species, which belongs to 55 families were documented along with their local names, part used and the use value of each species. This Data showed that highest number of plants used by local community belongs to Asteraceae Family. In our data Syzygium cumini (L.) Skeels has the highest use value that is 1 and the plants with lowest use value (0.2) are Eclipta alba (L.) Hassk, Ruellia tuberose L., Aerv javanica (Burm.f) juss. It is concluded from data that our study area possesses a variety of indigenous medicinal plants that are widely used by hakims, herbalists for primary health care of local community of Province Punjab, Pakistan.

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 categoriesInsufficient payload (model declined to judge)
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 score0.629
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.232
Teacher spread0.182 · 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 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

Citations5
Published2013
Admission routes1
Has abstractyes

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