Research progress in hepatic encephalopathy in recent 10 years: A Web of Science-based literature analysis.
Bibliographic record
Abstract
OBJECTIVE: To analyze international research trends in hepatic encephalopathy and examine the role of neuroelectrophysiology and neuroimaging in diagnosis of hepatic encephalopathy. DATA RETRIEVAL: We performed a bibliometric analysis of studies on hepatic encephalopathy published during 2002-2011 retrieved from Web of Science. INCLUSION CRITERIA: (1) peer-reviewed published articles on hepatic encephalopathy; (2) original article, review, meeting abstract, proceedings paper, book chapter, editorial material, news items, and (3) published during 2002-2011. EXCLUSION CRITERIA: (1) articles that required manual searching or telephone access; (2) documents that were not published in the public domain; and (3) corrected papers from the total number of articles. MAIN OUTCOME MEASURES: (1) Annual publication output; (2) type of publication; (3) publication by research field; (4) publication by journal; (5) publication by author; (6) publication by institution; (7) publication by country; (8) publication by institution in China; (9) most-cited papers. RESULTS: A total of 3 233 papers regarding hepatic encephalopathy were retrieved during 2002-2011. The number of papers gradually increased over the 10-year study period and was highest in 2010. Most papers appeared in journals with a focus on gastroenterology and hepatology. Among the included journals, Hepatology published the greatest number of papers regarding hepatic encephalopathy, and the published studies were highly cited. Thus, Hepatology appears to represent a key journal publishing papers on hepatic encephalopathy. Regarding distribution by country for publications on hepatic encephalopathy indexed in Web of Science during 2002-2011, the United States published highest number of papers, with China ranked ninth. As per distribution by institute for publications, the University of Montreal in Canada published the highest number of papers (n = 111). Among the Chinese institutes, Zhejiang University in China was the most prolific institute with 15 papers. CONCLUSION: The present bibliometric analysis on hepatic encephalopathy provides an overview of research progress, as well as identifying the most active institutes and experts in this research field during 2002-2011. Research into hepatic encephalopathy has revealed changes in neural injury and regeneration in hepatic encephalopathy. Neuroelectrophysiological and neuroimaging examinations are important for determining clinical classifications and disease severity of hepatic encephalopathy, providing a foundation for further research.
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How this classification was reachedexpand
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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.140 | 0.164 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".