Bibliographic record
Abstract
Objectives: One of the most important aspects of Qi Gong practice is to understand self-care and self-discipline as a practitioner’s service both to themself and to others. Self-care and self-discipline is physical, mental, and spiritual. By understanding one’s responsibility in this way, practitioners are free to practice medicine as a relationship between themselves and patients, helping them to become a healer.Methods: Traditional Chinese Medicine as a philosophy and practice will be introduced in the context of developing a successful Qi Gong practice. Basic Qi Gong techniques in posture, movement, breathing, phonation, and visualization will be demonstrated interactively. Increasing self-awareness will be emphasized, so that practitioners can use Qi Gong techniques to develop healing skills in their medical practice.Results: Although it requires long-term commitment to receive many of the deeper rewards of a dedicated Qi Gong practice, many of the early benefits are possible with only a modest investment in performing proper Qi Gong techniques. Practitioners will learn to increase their mindfulness and concentration, and understand the value of self-care and self-discipline. Through short practice sessions, the utility of Qi Gong in improving healing will become evident to the novice and initiated alike.Conclusions: Qi Gong is a series of ancient techniques from Traditional Chinese Medicine that promote self-care and self-discipline as a service to oneself and others. Qi Gong is a valuable method for taking care of oneself, and also allows practitioners to transfer its benefits to patients during the compassionate practice of medicine. It forms a foundation for whole person care by strengthening practitioners to provide healing to patients on the physical, mental, and spiritual levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".