Interventions for improving the productivity and environmental performance of global aquaculture for future food security
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
Aquatic foods are increasingly being recognized as having an important role to play in an environmentally sustainable and nutritionally sufficient food system. Proposals for increasing aquatic food production often center around species, environments, and ambitious hi-tech solutions that mainly will benefit the 16% of the global population living in high-income countries. Meanwhile, most aquaculture species and systems suffer from large performance gaps, meaning that targeted interventions and investments could significantly boost aquatic food supply and access to nutritious foods without a concomitant increase in environmental footprints. Here we contend that the dialogue around aquatic foods should pay greater attention to identifying and implementing interventions to improve the productivity and environmental performance of low-value commodity species that have been relatively overlooked in this regard to date. We detail a range of available technical and institutional intervention options and evaluate their potential for increasing the output and environmental performance of global aquaculture.
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) | 0.000 | 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) | 0.000 | 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