Fog Computing Research: A Scientometric Assessment of Global Publications Output During 2012–18
Bibliographic record
Abstract
The present study has examined fog computing global research output, as indexed in Scopus database during 2012–18 on a series of bibliometric measures, such as publications growth rate, global publications share, citation impact, the share of international collaborative papers, distribution of publications by broad subjects. In addition, the study discusses the citation profile of top organizations and authors in fog computing, and the preferred media for research communication and characteristics of highly cited papers. The study finds 1711 global research output registered (68.09%) annual growth rate. 81 countries participated in fog computing research, of which the top 10 countries accounted for 91.23% global publication share and more than 100% of global citation share during 2012–18. China and USA tops the list of top 10 most productive countries in fog computing research with 22.38% and 19.40% global publication share, followed by India (9.70%), Italy (7.36%), Australia (6.14%), etc. USA top the list (17.02% and 2.25%), followed by Australia (15.54% and 2.06%), UK (12.09% and 1.59%), Canada (11.03% and 1.46%), Spain (9.95% and 1.32%), etc. in terms of citation impact per paper and relative citation index. 401 organizations and 457 authors participated in global fog computing research, of which the top 10 organizations and authors contributed (15.02% and 7.48%) global publication share and (42.17% and 12.81%) global citations share during 2012–18. The world contributed (59.75%) share of output in fog computing research in top 20 most productive journals, and 19 of its papers have been rated as highly cited papers each with 100 to 1657 citations per paper, averaging 209.79 citations per paper
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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 | Observational | high |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, 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".