Bibliographic record
Abstract
A call for papers for the BMJ theme issue on eHealth applications Over the past decade, we have been exposed to an unprecedented number of information and communication technologies that have promised to affect health care. We have witnessed the breathtaking expansion of the internet and the launch of numerous personal electronic assistants, with smart phones and wireless personal organisers leading the pack. Most high income countries have allocated substantial resources to integrating electronic health information systems and many of their citizens now have access to the internet. During the same decade some disturbing changes took place. Most “dot com” companies rose and fell, leaving their promises for radical change unfulfilled. In the countries with the requisite tools and the infrastructure, doctors continued …
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.019 | 0.032 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.023 | 0.026 |
| Insufficient payload (model declined to judge) | 0.056 | 0.022 |
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".