Krill diel vertical migration fine dynamics, nocturnal overturns, and their roles for aggregation in stratified flows
Bibliographic record
Abstract
A set of high-resolution observations on short-term dynamics of krill diel vertical migrations (DVM) in the St. Lawrence Estuary are presented here, including vertical mass transfer measurements from multifrequency echo sounding coupled with stratified net sampling and tracers of individual vertical movements from stomach pigments over a 72 h period. The data set is supplemented by vertical migration speeds and biomass diel patterns from ADCP (acoustic Doppler current profiler) time series lasting up to 3 months. All krill always rapidly migrated to the surface in synchrony at sunset. Soon after the ascent, fed krill started to swim downward. A scattering layer was then formed at their daytime depth with sometimes a significant backscatter at intermediate depths, especially around midnight. A reorganisation in the upper water column then occurs, likely for a predawn feeding bout. At dawn, the krill mass still feeding in upper water column synchronously swam downward to their daytime depth. This nocturnal asynchronous vertical behaviour, conforming to the DVM hunger-satiation hypothesis, repeated between August and October in two different years, the DVM timing being determined by day length.
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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 | 0.001 | 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 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".