System Dynamics Of The Barents Sea Capelin
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The capelin (Mallotus villosus) has a northerly circumpolar distribution. In the Atlantic the capelin is located in the Barents Sea, Iceland, Greenland, Labrador and Newfoundland. The capelin stock in the Barents Sea is the largest in the world and has a key role in the Arctic food chain. The large fluctuations of the biomass have been poorly understood and collapses in the biomass have been registered. In the presented paper a system analysis of the capelin stock has identified a state dynamic model and a frequency dynamic model of the stock properties. The results show the capelin stock dynamics is adapted to the deterministic 18.6 yrs and 18.6/3=6.2 yrs Earth nutation cycles. The most important cycle is the 6.2 yrs cycle, which is identified in the recruitment, maturity and growth. A frequency transform of the estimated model shows a stochastic resonance at about the half of the 6.2 yrs cycle. The stochastic resonance shows that fluctuation of stock number is a natural adoption to the environment and a strategy for optimal growth and survival in the long run. In this stochastic resonance is timing between stock number fluctuation and the 6.2 yrs cycle of most importance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".