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Record W4317240827 · doi:10.56726/irjmets33003

ALTERNATIVE MEDICINE: THERAPIES AND TREAT THE DISEASES BY NEW WAYS

2023· article· en· W4317240827 on OpenAlexaff
Nitish Kumar Drivedi, Deepak Chaurasia, Tarkeshwar P. Shukla

Bibliographic record

VenueInternational Research Journal of Modernization in Engineering Technology and Science · 2023
Typearticle
Languageen
FieldMedicine
TopicMedical and Biological Ozone Research
Canadian institutionsMcMaster University
FundersNational Center for Complementary and Alternative MedicineNational Institutes of Health
KeywordsMedicineAlternative medicineIntensive care medicineEngineering ethicsEngineeringPathology

Abstract

fetched live from OpenAlex

Alternative medicine is a term that describes medical treatments that are used instead of traditional (mainstream) therapies.Some people also refer to it as "integrative" or "complementary" medicine.Alternative medicine is the most widely used remedy systems, in the treatment of various diseases.Alternative medicine is used widely because there are a large health care alternatives to be more congruent within the own values and beliefs towards health.Alternative medicine is more compatible with patients, offers more personal autonomy and control over the health care decisions.It is accepted worldwide because of its compatibility and acceptability in increasing the beliefs regarding the nature and meaning of health and illness.This review deals with various alternative therapies used such as Ayurveda, homeopathy, acupuncture, naturopathy, yoga, herbal medicine, massage therapy; effectiveness of the alternative medicine; assessment of the effectiveness of alternative medicine; sources of information about the alternative medicine; alternative medicine therapies in treatment of various diseases; perceived benefits of alternative medicine and thereby concluding with the increased level of acceptance of alternative medicine, its widespread use in various diseases and their treatment with various alternative therapies.

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)0.002
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.005
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0110.004

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 head0.072
GPT teacher head0.388
Teacher spread0.316 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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