Entrainment and advection in an island's tidal wake, as revealed by light attenuance, zooplankton, and ichthyoplankton
Bibliographic record
Abstract
Spatial and temporal patterns of light attenuance, zooplankton abundance, and larval fish assemblages observed at night in the flood tide wake of a 2‐km‐wide, steep‐sided island within the Great Barrier Reef lagoon (40–45‐m local depth) are compared with two simple models. Eddy upwelling is shown to be slow relative to erosion, vertical entrainment, and advection (EA) arising near the flanks of the island, where currents were accelerated to 1–2 m s−1, approximately twice that in the free stream. Turbidity (particles <300‐µm equivalent spherical diameter [ESD], inferred from increased water column light attenuance of an optical plankton counter) and medium‐sized zooplankton (700–1,000‐µm ESD) appeared to be entrained toward the surface, to form a V‐shaped plume. The plume originated near the island's flanks and converged 4 km downstream. Here, light attenuance returned to the free stream conditions, presumably as sediments settled, leaving a patch of medium‐sized zooplankton that had a three‐ to fourfold greater biomass concentration than the free stream. A decrease in the concentration of small zooplankton (300–500‐µm ESD, generally found in surface waters) is also consistent with vertical mixing by EA. Neuston net collections across the wake revealed two larval fish assemblages that were correlated with either the small surface zooplankton or with the deeper, medium‐sized zooplankton, which included epibenthic taxa. If EA is a common process for patch formation in tidal waters, then the geometry of the associated plumes may predict larval settlement (recruitment “hotspots”) in shallow tidal waters.
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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) | 0.000 | 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".