Has Embase replaced MEDLINE since coverage expansion?
Bibliographic record
Abstract
OBJECTIVES: The research tested the authors' hypothesis that more researchers from the academic medicine community in the United States and Canada with institutional access to Embase had started using Embase to replace MEDLINE since Embase was expanded in 2010 to cover all MEDLINE records. METHODS: We contacted libraries of 140 and 17 medical schools in the United States and Canada, respectively, to confirm their subscriptions to Embase 5 years before and 5 years after 2010. We searched the names of institutions with confirmed Embase access in Ovid MEDLINE and Embase to retrieve works authored by affiliates of those institutions. We then examined 100 randomly selected records from each of the 5 years before and 5 years after the Embase coverage expansion in 2010. We hypothesized that studies that used Embase but not MEDLINE would increase due to the Embase coverage expansion. RESULTS: The number of studies that used Embase but not MEDLINE did not change between the pre-2010 and post-2010 periods. CONCLUSION: Our hypothesis was refuted. Studies that used Embase but not MEDLINE did not increase post-2010. Our results suggest the academic medicine community in the United States and Canada that had access did not use Embase to replace MEDLINE, despite the Embase coverage expansion.
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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 | 0.106 | 0.303 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.031 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".