Body size–density relationship for <i>Mytilus edulis</i> in an experimental food‐regulated situation
Bibliographic record
Abstract
We grew mussels ( Mytilus edulis ) under two different food regimes and eight population density levels to estimate the joint effects of density and biomass on their growth and survival and to determine the shape of the biomass–density ( B–N) relationship. Mussels were reared for 22 months, between December 1994 and October 1996, in 1‐L experimental chambers supplied with natural seston. Growth in shell length, individual wet mass and ash free dry mass ( m ) decreased with decreasing food availability and increasing population density. Survival was negatively correlated with density but did not differ significantly between food regimes during the first year. Variations in concentration of available food did not alter the effects of crowding on mussels, as judged from the slopes of the body size–density curves. The general patterns exhibited by B–N curves were not consistent with expectations since we found 1) no classical competition–density (C–D) effect as reported in plants at intermediate competition levels, and 2) a slope of −0.648 for m–N curves in both food regimes, which was higher than expected from self‐thinning (ST) theory. This value does not support present food‐driven ST theory. This study introduces an unusual m–N region which combines properties of both ST and C–D effect.
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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 | 0.000 |
| 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 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".