<i>Ulva prolifera</i> green-tide outbreaks and their environmental impact in the Yellow Sea, China
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
green tides in the Yellow Sea, China, which have been occurring since 2007, are a serious environmental problem attracting worldwide attention. Despite extensive research, the outbreak mechanisms have not been fully understood. Comprehensive analysis of anthropogenic and natural biotic and abiotic factors reveals that human activities, regional physicochemical conditions and algal physiological characteristics as well as ocean warming and biological interactions (with microorganism or other macroalgae) are closely related to the occurrence of green tides. Dynamics of these factors and their interactions could explain why green tides suddenly occurred in 2007 and decreased abruptly in 2017. Moreover, the consequence of green tides is serious. The decay of macroalgal biomass could result in hypoxia and acidification, possibly induce red tide and even have a long-lasting impact on coastal carbon cycles and the ecosystem. Accordingly, corresponding countermeasures have been proposed in our study for future reference in ecosystem management strategies and sustainable development policy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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