A cross-sectional description of open access publication costs, policies and impact in emergency medicine and critical care journals
Bibliographic record
Abstract
Introduction: Finding journal open access information alongside its global impact requires access to multiple databases. We describe a single, searchable database of all emergency medicine and critical care journals that include their open access policies, publication costs, and impact metrics. Methods: A list of emergency medicine and critical care journals (including citation metrics) was created using Scopus (Citescore) and the Web of Science (Impact Factor). Cost of gold/hybrid open access and article process charges (open access fees) were collected from journal websites. Self-archiving policies were collected from the Sherpa/RoMEO database. Relative cost of access in different regions were calculated using the World Bank Purchasing Power Parity index for authors from the United States, Germany, Turkey, China, Brazil, South Africa and Australia. Results: We identified 78 emergency medicine and 82 critical care journals. Median Citescore for emergency medicine was 0.73 (interquartile range, IQR 0.32-1.27). Median impact factor was 1.68 (IQR 1.00-2.39). Median Citescore for critical care was 0.95 (IQR 0.25-2.06). Median impact factor was 2.18 (IQR 1.73-3.50). Mean article process charge for emergency medicine was $2243.04, SD = $1136.16 and for critical care $2201.64, SD = $1174.38. Article process charges were 2.24, 1.75, 2.28 and 1.56 times more expensive for South African, Chinese, Turkish and Brazilian authors respectively than United States authors, but neutral for German and Australian authors (1.02 and 0.81 respectively). The database can be accessed here: http://www.emct.info/publication-search.html. Conclusions: We present a single database that captures emergency medicine and critical care journal impact rankings alongside its respective open access cost and green open access policies.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | BibliometricsScholarly communicationOpen science Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| gpt | BibliometricsScholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.011 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".