Bibliographic record
Abstract
The hemophilias are the most common X-linked inherited bleeding disorders, and if not managed properly, they can lead to chronic disease and lifelong disabilities. The hemophilias remains a hot topic in the field of hematology. This bibliometric study aimed to investigate the current status of publications on haemophilia. The goal of this study was to retrieve data from journals that were indexed in the Web of Science (WoS; Thomson Reuters, New York, NY, USA) database. Keywords related to “Hemophilia” were used. The time span was set from 1970 to 2021. Data pertaining to growth of publications, the most active countries and institutions, the most cited journals, and mapping of publications and keywords were analyzed. Retrieved data were analyzed to present various bibliometric indicators while maps were visualized using the VOS viewer technique. The Hirsch (H) index and the impact factor (IF) of the publishing journal were used as indicators of impact of publications. A total of 7.736 articles were retrieved with an average of 22.06 and total of 170.624 citations. H index was found as 149. Study searches the publications in the period between 1970 and 2020 first article was in the year 1970. The leading country on journal number is the United States of America (USA) with (n=2474; 31.98%), followed by England (11.69%), Germany (9.76%), Italy (8.59%), Canada (6.81%), France (6.67%). Most of the retrieved articles were from research areas of Hematology (n=4706; 60.83%), Cardiovascular System/Cardiology (11.46%), General Internal Medicine (10.12%), Pediatrics (4.52%), Genetics Heredity (n4.25%). The number of publications from the development countries should be increased and research on hemophilia should be supported. The landscape of this illness is changing continuously, and bibliometric studies like the one presented are a useful tool for highlighting developments inside this field.
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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 | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".