The Italian contribution to pediatric sleep medicine: A scientometric analysis
Bibliographic record
Abstract
We conducted the first scientometric analysis to quantitatively assess the scientific contribution of researchers from Italian institutions in the field of pediatric sleep medicine. We searched Science Citation Index Expanded from Web of Science (WOS) Science Citation up to November 3rd, 2022. Bibliometrix R packages (3.1.4) and CiteSpace (6.0.R2) were used to extract and analyze co-citation reference networks, co-occurring keyword networks, co-authorship network, co-cited institutions, and co-cited journals. We retrieved a total of 2499 documents, published between 1975 and 2022. Co-cited reference networks showed four main clusters of highly cited topics: evidence synthesis of publications on sleep disorders in children and adolescents, sleep and neurological disorders, non-pharmacological treatments of sleep disturbances, and sleep and Covid-19 in youth. Co-occurring keyword networks showed an earlier focus on the neurophysiology of sleep/neurological disorders, followed by a trend on the association of sleep disturbances to neurodevelopmental disorders and behavioral aspects. Co-authorship network showed that Italian researchers in the field of pediatric sleep medicine tend to be highly collaborative internationally. Overall, Italian researchers have provided a crucial contribution to pediatric sleep medicine across a number of specific topics, spanning from neurophysiology to treatment, and from neurological to behavioral/psychopathological aspects.
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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 | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.048 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".