"Essential fatty acids" in aquatic ecosystems: a crucial link between diet and human health and evolution
Bibliographic record
Abstract
Fatty acids (FA) are inextricably linked with key physiological and biochemical processes and are thus integral to proper ecosystem functioning. FA not biosynthesized effectively by animals are termed essential fatty acids (EFA). These EFA are important "drivers" of ecosystem health/stability and are therefore highly conserved in aquatic food chains. Aquatic organisms have been and continue to be our primary source of readily available EFA. However, overfishing and our burgeoning population may be acting in concert to threaten our access to this source of EFA. Here, we review the marine FA synthesis/transport cycle and traditional and nontraditional sources of EFA. Our review suggests that, while some traditional sources of marine oils (e.g., tuna) are in steady decline, other sources (e.g., krill) and technologies (e.g., heterotrophic fermentation) hold great promise for maintaining our access to EFA. We provide a minireview which illustrates that EFA contribute to our health and well-being. Finally, there is growing evidence that EFA have been an important force in our past evolution, leading us and others to speculate that an unbroken link exists between EFA, our present health, and, in all likelihood, our continuing evolution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".