Bibliographic record
Abstract
Since Michael Balint in the 1950s much reflection and comment has occurred on the concept of the consultation.1 Now cohort after cohort of medical students benefit from ever greater exposure to communication ideas leaving their more qualified colleagues running to catch up. Little, though, has been said about the physical examination. This is remarkable. The physical examination forms part of our earliest clinical experience but has had little focus in my professional development since then. I believe that the evolution in our communication skills has more to contribute to the physical examination of our patients and the physical examination has more to contribute to the consultation than is commonly identified. Balint said ‘Our patients are trained from childhood to expect a more or less thorough physical examination.’1 Patients intermingle telling their story and the doctor's examination, and see these as two parts of a whole. I examine sometimes to meet patient expectation. Although there are patients who prepare for a physical examination (going home to wash) and I only identify this as I am closing the consultation, how many others will have left without this expectation being understood and met? But a physical examination does more than address patient expectation. The acknowledged significance of physical examination is in finding physical signs. There are decades of medical undergraduate education committed to this. Although the ‘thorough physical examination’ was a 20th century phenomenon, before that, ‘the physician's job was not hands on: what counted were book learning, experience, memory, judgement and a good bedside manner’.2 In the diagrammatic representation of the Cambridge Calgary model3 of the consultation, …
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.039 | 0.008 |
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".