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
Sea-surface warming, sea-ice melting and related freshening, changes in circulation and mixing regimes, and ocean acidification induced by the present climate changes are modifying marine ecosystem structure and function and have the potential to alter the cycling of carbon and nutrients in surface oceans. Changing climate has direct and indirect consequences on marine viruses, including cascading effects on biogeochemical cycles, food webs, and the metabolic balance of the ocean. We discuss here a range of case studies of climate change and the potential consequences on virus function, viral assemblages and virus-host interactions. In turn, marine viruses influence directly and indirectly biogeochemical cycles, carbon sequestration capacity of the oceans and the gas exchange between the ocean surface and the atmosphere. We cannot yet predict whether the viruses will exacerbate or attenuate the magnitude of climate changes on marine ecosystems, but we provide evidence that marine viruses interact actively with the present climate change and are a key biotic component that is able to influence the oceans' feedback on climate change. Long-term and wide spatial-scale studies, and improved knowledge of host-virus dynamics in the world's oceans will permit the incorporation of the viral component into future ocean climate models and increase the accuracy of the predictions of the climate change impacts on the function of the oceans.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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