Morpho-sedimentary characterization of intertidal seagrass Zostera noltii (Horneman, 1832) in relation to biometric indicators.
Bibliographic record
Abstract
Zostera noltii (Horneman, 1832) intertidal seagrass is one of the two marine phanerogams species occuring along the North-Atlantic coasts. This seagrass growths on muddy-sand flats in sheltered environments such as estuaries and protected embayments. Z. noltii has a significant biomass which is varying with its geographical distribution. In North Brittany coast of France, the average biomass reaches 120 g.dw.m-2 with a productivity around 500 g.C.m-2.y-1. These biocoenoses are listed among the most productive marine ecosystems. The physical structure of the seagrass beds contributes to fine particles deposition, while locally reducing tidal currents. Temporal and spatial variations of seagrass beds structure depends on physical and biological factors. Alternating periods of erosion and sedimentation affect the superficial sediment stability and consequently the seagrass meadows development. After a strong erosion stage, the beds recovery is going on for 5 to 10 years. However, Z. noltii seems rather tolerant to the annual sediment budget fluctuations. Arenicola marina contributes to important bioturbation which can locally scraps the seagrass beds. The occurence of Z. noltii seagrass influences the morpho-sedimentary dynamic of the surrounding area, although, this sedimentary environment induces the seagrass meadows structure.
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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".