Is limnology becoming increasingly abiotic, riverine, and global?
Bibliographic record
Abstract
Abstract Scientists often debate on the evolving state of their fields and future research directions, but empirical studies on research trends are rare and this limits our capacity to disentangle perceptions from facts within the mass of available data. We used ecological and paleolimnological approaches to assess how the “community” of words most commonly used in limnological studies presented at the Association for the Sciences of Limnology and Oceanography (ASLO) meetings and published in Web of Science have evolved over the last decades. We found that the field of limnology has become increasingly focused on global abiotic research themes, especially in rivers, while there was a decrease in the proportion of organismal studies. We hypothesize that this results from both major influential publications highlighting the importance of framing limnology in a global context and the methodological limitations of organismal studies that prevent data from scaling up as quickly as their abiotic counterparts.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".