Bibliographic record
Abstract
Clinical practice guidelines are consensus statements systematically developed to help physicians, and ultimately patients, make decisions about appropriate health care for specific clinical circumstances. Over 20 years ago the American College of Cardiology (ACC) and the American Heart Association (AHA) established a joint task force to define the role of specific, non-invasive and invasive procedures in the diagnosis and management of cardiovascular disease.1 More specifically, this was initially aimed at establishing the appropriate utilisation of technology in the diagnosis and treatment of cardiovascular patients and was initially directed towards the development of guidelines for permanent cardiac pacemaker implantation. Subsequently, task forces have played an important role in developing other guidelines for a host of cardiovascular, medical, and surgical conditions as well as diagnostic procedures. Using rules of evidence and clinical recommendations originally developed by Sackett for the use of antithrombotic agents, a relatively systematic approach (see box) towards the generation of guidelines has emerged.2 Framed by three levels of evidence, recommendations are categorised as: (1) data derived from multiple randomised clinical trials; (2) data derived from a single randomised trial or non-randomised studies; and (3) where data does not exist but a consensus opinion is developed from a variety of experts. When recommendations emerge from consensus opinion, these often emanate from strongly held and sometimes diverse views giving some substance to the perspective of Abba Eban, former Israeli Ambassador to the United Nations, who suggested that “consensus means that lots of people say collectively what no one believes individually”. Approximately 25 such guidelines have emerged since the ACC/AHA commenced joint production of these in 1980 making it difficult to stay abreast of the volume of recommendations. Indeed, as recently reported by Ohman and Peterson, even within the three guidelines for ischaemic heart disease encompassing chronic stable angina, unstable …
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".