Distribution of mollusc larvae in the estuarine complex of Paranaguá Bay (Paraná, Brazil) (Lat. 25° 15’ - 25° 30’s)
Bibliographic record
Abstract
The spatial distribution of mollusc larvae was investigated in the estuarine complex of Paranaguá Bay (SE Brazil).Plankton samples were collected during April using horizontal tows of 1 minute duration, during the ebb and fl ood tides, at 06 (six) points on the estuary and at two depths (surface and bottom).A conical plankton net was used (mesh size: 225 µm; mouth diameter: 30 cm) and the samples were preserved in 4% buffered formaldehyde and sorted under a stereoscopic microscope.The biological results were analyzed, through PCA (Principal Component Analysis), to gather data for temperature, salinity, current velocity, turbidity and chlorophyll-a, and the variability in the number of larvae between locations, depths and tidal phases was compared by multifactorial ANOVA.Oyster larvae (Crassostrea sp.) were more abundant (p<0.05) in those locations with greater hydrodynamic forces (entrance to the estuary) and during the fl ood tide.Other bivalves and gastropods, negatively correlated with salinity, were more present in those locations with weaker hydrodynamic forces (interior of the bay).The marked presence of the three categories of larvae close to the bottom demonstrates the behaviour of larvae near settling stage.
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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 | 0.001 |
| 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".