Bibliographic record
Abstract
Evolve osteoporosis and other guidelines avoiding cognitive biasEvolve, the Royal Australasian College of Physicians' (RACP) equivalent of the American Board of Internal Medicine (ABIM) Foundation's Choosing Wisely campaign, was launched in 2015.The aim of these campaigns is to demonstrate to the community the profession's tangible commitment to its social justice principles, 1 which include effecting responsible stewardship of entrusted resources.Unfortunately, early indications are that the RACP programme is taking the same pathway to failure as the initial phases of the ABIM campaign suggesting the need for a reset.As a percentage of gross domestic product (GDP), inflation-adjusted expenditure for health care in Australia, New Zealand and the United Kingdom has continuously increased for 20 years. 2 In real terms, for the period 2009-2014, the average annual growth in per capita health spending in Australia was 2.0% (down from 2.9% in the preceding 5-year period) while in New Zealand, it was 0.6% (down from 4.1%).As a percentage of GDP, in 2014, Australia, New Zealand and the United Kingdom spent 9.4, 11.0 and 9.1% of their respective GDP on healthcare compared to 20 years earlier when each spent circa 7%.In New Zealand, there was a sharp rise from 8.4% in 2007 to 10.7% in 2008.The ABIM Foundation launched the Choosing Wisely campaign in 2012 3 encouraging specialty groups to adopt the 'Top Five' list approach.This approach encouraged the identification of five diagnostic tests or treatments that are amongst the most expensive and commonly ordered by members of a specific specialty but which have been shown by currently available evidence to provide no meaningful benefit to significant categories of patients.4 Over 12 OECD countries have adopted similar programmes.The primary goal is to reduce waste in the healthcare system and avoid risks associated with unnecessary treatment.At the second RACP sponsored Evolve meeting in Sydney on 7 April 2016, several medical specialty societies adopted the choosing wisely approach and presented their lists of low-value tests or procedures.Several items were duplications of ABIM counterparts.1.The statements are outward looking.2. The statements are educational with no significant measurable impact.
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 | 0.023 | 0.214 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".