Experimental assessments of marine species sensitivities to ocean acidification and co-stressors: how far have we come?
Bibliographic record
Abstract
Experimental studies assessing the potential impacts of ocean acidification on marine organisms have rapidly expanded and produced a wealth of empirical data over the past decade. This perspective examines four key areas of transformative developments in experimental approaches: (1) methodological advances; (2) advances in elucidating physiological and molecular mechanisms behind observed CO 2 effects; (3) recognition of short-term CO 2 variability as a likely modifier of species sensitivities (Ocean Variability Hypothesis); and (4) consensus on the multistressor nature of marine climate change where effect interactions are still challenging to anticipate. No single experiment allows predicting the fate of future populations. But sustaining the accumulation of empirical evidence is critical for more robust estimates of species reaction norms and thus for enabling better modeling approaches. Moreover, advanced experimental approaches are needed to address knowledge gaps including changes in species interactions and intraspecific variability in sensitivity and its importance for the adaptation potential of marine organisms to a high CO 2 world.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".