ICES Report: Increasing Access to Health Administrative Data with ICES Data & Analytic Services
Bibliographic record
Abstract
The Institute for Clinical Evaluative Sciences (ICES) is one of only a few organizations in Ontario permitted to access, link and analyze health administrative data for the purpose of generating evidence to inform decisions in policy and practice. Although ICES is a leading research institute, its access to the data has historically been restricted to scientists with an ICES affiliation. This requirement, designed to meet ICES' data privacy and security obligations, created barriers with respect to the widespread use of Ontario's data assets. In 2014, as part of the government's commitment to the Strategy for Patient-Oriented Research, ICES launched the Data & Analytic Services platform, which is aimed at increasing access to data and analytic services to investigators external to ICES. In making the data widely available to the broader research community, this initiative engages investigators involved in front-line care, stimulates new avenues of research and fosters collaboration that was previously challenging or unfeasible.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".