The spatiotemporal variability of phytoplankton phenology in the Caspian Sea (an ecoregion-based approach)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental perturbations caused dramatic changes in the Caspian Sea’s phytoplankton phenology, with severe consequences for ecosystem health and functioning. To better understand these changes, phenological properties of main phytoplankton blooms were quantified using satellite-derived chlorophyll-a (1998–2015). Results showed significant ecoregion-scale differences in blooms’ timing, duration, magnitude and interannual variability (p < 0.05), especially in north-eastern and southern ecoregions, suggesting their high sensitivity to recent environmental changes. Given the ecological and socio-economic importance of north-eastern and southern ecoregions and the influence of temperature in bloom timing changes, this study suggests ecosystem managers and policymakers focus on future impacts of climate change on these ecoregions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it