Socioeducational Observation in Breathwork: Bibliometrics for Rochrematic
Bibliographic record
Abstract
The modern digital era brings a problem that has a direct impact on physical and mental health, mainly in young people and adults related to stress, which promotes new health workers to take new care measures such as “yoga” Objective: To describe the scientific production of the topic Breathwork from 2021 to 2025 according to the type of document, category, editors, year of publication, country and language. Method: it was a bibliometric analysis in Web of Science in the Journal Citation Report platform, with the search syntax in English “Breathwork” the search was in all fields. Results: 52 publications, mainly articles (44), review articles (5), meeting summary (2), book under review (1). Its categories in Web of Science are Psychiatry (10), Neurosciences (7), Clinical Psychology (6). Integrative Complementary Medicine (5). Experimental Research Medicine (5). Multidisciplinary Sciences (4). Multidisciplinary Psychology (4). Pharmacology Pharmacy (3). Gastroenterology Hepatology (2). Health Sciences Services (2). Humanities Multidisciplinary (2). Linguistics (2). Elsevier Publishers (11). Taylor & Francis (7). Springer Nature (6). Frontiers Media Sa (3). Mdpi (3), among others (22). and by year was in 2023: (17). 2024 (15). y 2022, (10). 2021, (8). y 2025 (2). The countries with the highest production are USA, (26). England, (11). Canada, (6), Germany, (4), Australia, (3), Poland, (2). Also, the predominant language is English (52) in these publications. Conclusions: The results show low performance in scientific production on the topic of “Breathwork”.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | Bibliometrics 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 | 0.022 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.129 | 0.142 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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.
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".