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Record W4387718524 · doi:10.58396/bephs020105

Traditional medicine in the developing and developed countries and expected trends in future

2023· article· en· W4387718524 on OpenAlexfundno aff

Bibliographic record

VenueBiomedicine Engineering and Public Health Studies · 2023
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
FundersUniversity of KarachiUniversity of Calgary
KeywordsDeveloping countryEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Traditional Medicine has been practiced all through the whilst in almost all Countries imparting treasured health care.Traditional drugs have been utilized locally accessible plant, animal, and mineral supplies and proceed to supply health Care to humans in many developing countries.Traditional Medicine ™ developed with time and continued to be the primary health service of rural communities and the poorest stages of society.Presently there is a developing reliance on regular health care using city populations.WHO defines frequent treatment as diverse health practices, approaches, knowledge, and beliefs incorporating plant animal, and/ or mineral-based medicines, spiritual therapies, information techniques, and exercising routines utilized singularly or in combination to keep well-being as appropriate as to treat, diagnose or prevent illness" In Asia, there are formalized traditions/systems which have theoretical frameworks.Including twisted educational traditions, formalized learning processes, written materials, heavily drugged medicine and scientific practices with many preventive and curative modalities.Traditional Chinese

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.181
GPT teacher head0.387
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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