Research on the Construction of Clinical Teaching Curriculum Based on the Cultivation of Students' Communication Consciousness
Bibliographic record
Abstract
Doctor and nursing students-patient communication belongs to the non-technical category of doctor and nursing students-patient relationship, which is one of the important contents of doctor and nursing students-patient relationship, including social, psychological and legal relations between doctor and nursing studentss and patients, and has become a prominent problem in current medical and health reform. Therefore, cultivating medical students' ability of doctor and nursing students-patient communication and guiding medical students to establish a harmonious doctor and nursing students-patient relationship has become a serious and urgent task for our clinical teaching teachers. Therefore, cultivating medical students' ability of doctor and nursing students-patient communication and guiding medical students to establish a harmonious doctor and nursing students-patient relationship has become a serious and urgent task for our clinical teaching teachers. In clinical teaching, students of traditional Chinese medicine should put themselves in other's shoes and communicate with patients. Instead of treating patients as a complex of flesh, blood vessels and bones, they should treat patients as an independent individual who not only has body but also has more thoughts, inject humanistic care into the doctor and nursing students-patient relationship, respect their psychological feelings and legal rights, and gradually realize that doctor and nursing students-patient communication is the theme of doctor and nursing students-patient relationship.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".