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Record W4321513455 · doi:10.38205/imcr.030102

Integrative Healthcare in India: A Paradigm Shift in Modern Medical Education and Practice of 21st Century

2022· article· en· W4321513455 on OpenAlexaboutno aff
Vivek Podder, Akshay Anand

Bibliographic record

VenueIntegrative Medicine Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrative medicineAlternative medicineHealth careParadigm shiftMedicineMedical educationHealthcare systemEngineering ethicsPsychologyNursingFamily medicineEpistemologyPolitical scienceLawPathologyEngineering

Abstract

fetched live from OpenAlex

The famous Canadian physician William Osler once said that “the good physician treats the disease; the great physician treats the patient who has the disease.” Integrative health holds the same philosophy by bringing together conventional and complementary approaches in a coordinated care for the whole person (body, mind, spirit) rather than giving a specializing care to a particular organ system. Integrative health can be contrasted with alternative medicine in which a person takes nonconventional treatment instead of conventional medicine. According to the Consortium of Academic Health Centers for Integrative Medicine and Health, integrative medicine is defined as “the practice of medicine that reaffirms the importance of the relationship between practitioner and patient, focuses on the whole person, is supported by evidence, utilized all appropriate therapeutic and lifestyle approaches, healthcare professionals and disciplines to achieve optimal health and healing.

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0060.022
Scholarly communication0.0080.005
Open science0.0020.006
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.030
GPT teacher head0.387
Teacher spread0.356 · 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 designTheoretical or conceptual
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

Citations1
Published2022
Admission routes1
Has abstractyes

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