Research trends in stable isotope ecology on unconsolidated intertidal ecosystems
Bibliographic record
Abstract
This study investigates the role of stable isotope ecology in unconsolidated sediment coastal systems, focusing on scientific production and research trends over time. Existing literature is analyzed to identify knowledge gaps and highlight the significance of stable isotope analysis in understanding coastal ecosystems. A comprehensive bibliometric analysis is employed, utilizing Scopus database to collect and categorize relevant publications on stable isotope ecology. Key indicators are focused on, including publication trends, authorship patterns, and the geographic distribution of research efforts. The temporal scale of studies is systematically analyzed, with attention given to methodological approaches used in these publications. Co-authorships networks and co-occurring keywords are examined to explore the intellectual structure of the field and identify collaborative patterns among authors. Over 140 publications are revealed, attributed to more than 400 researchers, with a significant increase in interest noted over time, particularly in trophic studies involving macrobenthos. Mudflats are identified as a focal point, receiving more attention than sandy beaches. The analysis indicates that seasonality is the predominant temporal scale, while mesoscale studies are observed to be more common in spatial investigations. A plateau in publication growth is noted, probably corresponding with the emergence of alternative methodologies for trophic ecology studies. Major contributions are attributed to France, the United States and Australia. Additionally, fragmented collaboration networks are illustrated through the co-authorship analysis, with limited international engagement among developing nations. Overall, the critical importance of stable isotope ecology in understanding coastal ecosystems is underscored, while the need for methodological diversity and increased collaboration in future research efforts is highlighted.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.012 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".