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Record W2114579678 · doi:10.5539/ach.v6n2p126

Thai Traditional Medicine: Applying Local Wisdom Knowledge for Health Treatment of Cancer Patients in Aphinyana Arokhayasala Foundation

2014· article· en· W2114579678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAsian Culture and History · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicGinger and Zingiberaceae research
Canadian institutionsnot available
FundersMahasarakham University
KeywordsMeditationFoundation (evidence)Alternative medicineBuddhismMedicineFamily medicineService (business)Health careIndigenousCancerNursingTraditional medicinePsychologyMedical educationPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Local wisdom knowledge concerning health care and treatment of cancer patientshas been handed down to Thai people who intent to study in this field. The Thai traditional practitioners working for Aphinyana Arokhayasala Foundation and using a Thai traditional medical examining and diagnosis to classify the patients into some kinds of cancer. They compound herbal medicine to treat their patients according to their symptoms and kinds of cancer. All patients staying in this Foundation are looked after by modern physicians, Thai traditional physicians, relatives, and service-minded volunteers and are treated with a combination of herbal medicine, exercise, and Buddhist meditation. This research will reflect all details of the application of indigenous knowledge for health treatment of cancer patients. Organizations concerned can use some ideas from the research results for treating their patients. Organizations concerned can use some ideas from the research results for treating their patients.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.420

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)0.0000.000

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 head0.137
GPT teacher head0.450
Teacher spread0.314 · 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