2015 Australian guidelines for the protection of health information
Bibliographic record
Abstract
The HISA Board of Directors is pleased to introduce HISA Guidelines for the Protection of Health Information, 2015 edition.\nThe 2015 edition of HISA’s Guidelines is the first publication of this work. It has been adapted under licence from the well regarded COACH Guidelines (2013) produced by COACH: Canada’s Health Informatics Association. All the contributors are experienced professionals who are actively engaged in the practice of privacy and security of health information locally, nationally, and internationally. The contributors have revised and updated an established and practical set of guidelines that are not only based on accepted standards and principles, but also pragmatic and easy to implement for any Australian healthcare professional or healthcare organisation.
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 | 0.034 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.027 | 0.017 |
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".