Light intensity, salinity, and host velocity influence presettlement intensity and distribution on hosts by copepodids of sea lice,<i>Lepeophtheirus salmonis</i>
Bibliographic record
Abstract
Intensity and distribution of presettlement by the copepodid of the sea louse, Lepeophtheirus salmonis, on smolts of its host Atlantic salmon, Salmo salar, were quantified for 27 infection regimes under controlled flume conditions. Each infection regime represented a level of interaction between three levels (low, medium, high) of the physical factors of light (10, 300, 800 lx), salinity (20, 27, 35), and host velocity (0.2, 7.0, 15.0 cm·s1). Light, salinity, and host velocity independently and interactively determined the distribution and number of presettled copepodids on hosts. Host surface area also influenced the number of attached preestablished copepodids. The distribution of presettled copepodids on the host body surface closely corresponded to that of settled copepodids and chalimi reported from other studies, with the greatest levels observed on the fins, in particular the dorsal, caudal, and pectoral fins. Copepodid presettlement occurred on the gills under all conditions. Differential presettlement, not selective mortality, probably produces the distribution pattern of settled stages seen in other studies.
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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".