Fine scale depth regulation of invertebrate larvae around coastal fronts
Bibliographic record
Abstract
Abstract Vertical migrations of zooplankters have been widely described, but their active movements through shallow, highly dynamic water columns within the inner shelf may be more complex and difficult to characterize. In this study, invertebrate larvae, currents, and hydrographic variables were sampled at different depths during and after the presence of fronts on three different cruises off the southern coast of South Africa. Internal wave dynamics were observed in the hydrographic data set but also through satellite imagery, although strong surface convergent currents were absent and thermal stratification was weak. During the first two cruises, fronts were more conspicuous and they preceded strong onshore currents at depth which developed with the rising tide. Vertical distributions of larvae changed accordingly, with higher abundances at these deep layers once the front disappeared. The third cruise was carried out during slack tides, the front was not conspicuous, deep strong onshore currents did not occur afterward and larval distributions did not change consistently through time. Overall, the vertical distributions of many larval taxa matched the vertical profiles of shoreward currents and multivariate analyses revealed that these flows structured the larval community, which was neither influenced by temperature nor chlorophyll. Thus, the ability to regulate active vertical positioning may enhance shoreward advection and determine nearshore larval distributions.
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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) | 0.001 | 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".