Open Access and Article Processing Charges in Cardiology and Cardiac Surgery Journals: a CrossSectional Analysis
Bibliographic record
Abstract
INTRODUCTION: Open access (OA) publishing often requires article processing charges (APCs). While OA provides opportunities for broader readership, authors able to afford APCs are more commonly associated with well-funded, high-income country institutions, skewing knowledge dissemination. Here, we evaluate publishing models, OA practices, and APCs in cardiology and cardiac surgery. METHODS: The InCites Journal Citation Reports 2019 directory by Clarivate Analytics was searched for "Cardiac and Cardiovascular Systems" journals. Sister journals of included journals were identified. All journals were categorized as predominantly cardiology or cardiac surgery. Publishing models, APCs, and APC waivers were defined for all journals. RESULTS: One hundred sixty-one journals were identified (139 cardiology, 22 cardiac surgery). APCs ranged from $244 to $5,000 ($244-5,000 cardiology; $383-3,300 cardiac surgery), with mean $2,911±891 and median $3,000 (interquartile range [IQR]: $2,500-3,425) across 139 journals with non-zero available APCs ($2,970±890, median $3,000, IQR: $2,573-3,450, cardiology; $2,491±799, median $2,740, IQR: $2,300-3,000, cardiac surgery). Average APCs were $3,307±566 and median $3,250 (IQR: $3,000-3,500) for hybrid journals ($3,344±583, median $3,260, IQR: $3,000-3,690, cardiology; $2,983±221, median $2,975, IQR: $2,780-3,149, cardiac surgery) and $1,997±832 and median $2,100 (IQR: $1,404-2,538) for fully OA journals ($2,039±843, median $2,100, IQR: $1,419-2,604, cardiology; $1,788±805, median $2,000, IQR: $1,475-2,345, cardiac surgery). Waivers were available for 51 (86.4%) fully OA and 37 (37.4%) hybrid journals. Seventeen journals were fully OA without APCs, one journal did not yet release APCs, and four journals were subscription-only. CONCLUSION: OA publishing is common in cardiology and cardiac surgery with substantial APCs. Waivers remain limited, posing barriers for unfunded and lesser-funded researchers.
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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 | MetaresearchScholarly communication Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Scholarly communicationOpen science 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 | 0.010 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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, 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".