'Primum non nocere'. Are we really keeping our patients safe? Interprofessional communication between CAM and medical practitioners
Bibliographic record
Abstract
'Teamwork and communication failures are the leading cause of patient safety incidents in health care' (Canadian Patient Safety Institute 2011) Use of complementary and alternative medicine (CAM) in Australia is considerable (MacLennan 2006, McCabe 2005, Xue 2007), with more than two-thirds of the adult population using at least one form of CAM, and 44% reporting visiting a CAM practitioner in the previous 12 months (Xue 2007). The growth of CAM has raised many issues within the literature, the most common relating to safety, efficacy and regulation of CAM (MacLennan 2006, Shorofi and Arbon 2010, Robinson and McGrail 2004, Goldman 2008, Wardle 2012, Pinto 2008, Spinks and Hollingsworth 2012). However, despite this, the Australian public have continued to seek CAM as a component of their health care, spending in excess of $4 billion annually (Xue 2007).
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 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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".