The Impact of International Research Collaborations on the Citation Metrics and the Scientific Potential of South American Palliative Care Research: Bibliometric Analysis
Bibliographic record
Abstract
Background: Progress in palliative care (PC) requires scientific advances which could potentially be catalyzed by international research collaboration (IRC). It is currently not known how often IRC occurs with PC investigators in South America. Objectives: To evaluate the percentage of South America journal articles on PC involving IRCs and the impact of these collaborations on the scientific potential the studies and on their citations. Methods: This was a bibliometric analysis of studies published between January 1, 1998, and December 31, 2017. A search of Pubmed, Embase, Lilacs, and Web of Science (WOS) was performed using the terms "palliative care," "hospice care," "hospices" and "terminal care," combined with the name of South America countries. The scientific potential was assessed by analyzing study design, characteristics of the journal and funding. IRCs were further subdivided in internal (within South America countries) and external (with countries outside South America). Findings: Of the 641 articles, 117 (18.2%) involved IRCs (internal: 18, 2.8%; external: 110, 17.2%). Articles with IRCs had higher median two-year citations in WOS (2 vs. 1, p < 0.001), Scopus (3 vs. 1, p < 0.001) and Google Scholar (4.5 vs. 2, p < 0.001) compared to articles without IRC. Moreover, they were more often funded (40.7% vs. 9.7%, p < 0.001), published in Pubmed-indexed (76.1% vs. 41.6%; p < 0.001) and in WOS-indexed (70.1% vs. 29.6%; p < 0.001) journals, and with study designs most often classified as clinical trial (5.1% vs. 1.0%; p = 0.002) and cohort (10.3% vs. 2.9%; p < 0.001) compared to articles without IRC. Conclusions: Studies with international research collaborations, both internal and external to South America, are more frequently cited and have characteristics with greater scientific potential than do studies without international collaborations.
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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 | 0.050 | 0.229 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.216 | 0.269 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".