Bibliographic record
Abstract
recall when I was an intern back in the mid-1980s while training in the psychiatric emergency department I was told, "See it, do it, teach it."Accordingly, I observed how the nurses and psychiatrists triaged and interviewed patients, who were distressed, sometimes suicidal or psychotic, living with co- Vol 1, No 2 (2014) proposed that formal course work and clinical experience with mentor guidance are equally important.Yet, without enabling the student/health care professional to find within herself the person she is, the one who can relate to other human beings in an authentic way, then the patient may sense something essential is missing.As Dr. Kearsley so elegantly described, one needs to embody these qualities and then they will flow naturally between the health care professional and the patient.One way to reach this way of being is through learning how to be mindful 9,10 , and this we assert can be taught in medical schools 11,12,13,14 .As Marsden et al. indicate in their commentary in this issue, it is one of many ways to learn how to be.■ International Journal of Whole Person Care
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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 | 0.012 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.035 | 0.061 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".