Population characteristics of the mangrove clam Polymesoda (geloina) erosa (solander, 1786) in the Chorao mangrove, Goa
Bibliographic record
Abstract
Mangroves are the tropical and sub tropical coastal and/or estuarine intertidal or island plant communities. Since the early history of mankind, mangrove ecosystems have played important role in the socio-economic development of coastal people in the Indo-Pacific region. This unique but fragile ecosystem has been providing firewood, charcoal, pole, tannin and some traditional medicine to the people of coastal areas. Edible marine bivalves (clams, mussels and oysters) are widely distributed and form a sustainable fishery along the Maharashtra, Goa and Karnataka coast of the west coast of India. They provide cheap source of nutritious food for the coastal people. The estuarine and backwater systems along Maharashtra, Goa and Karnataka coasts are characterized by rich fauna, notable among them are members of the bivalve molluscs. The clams belonging to the genera Meretrix, Polymesoda, Paphia, green mussel; Perna viridis and oyster; Saccostrea cucullata and Crassostrea gryphoides are abundantly available in the mangroves of the central west coast of India. Three species of the mangrove clams belonging to sub genus Geloina are reported from the Indo-Pacific region (Ingole @iet al@@. 1994). They are Polymesoda erosa, P. bengalensis and P. expansa. The distribution of P. bengalensis is restricted to the Bay of Bengal, whereas P. erosa, and P. expansa are known to occur along the east as well as west coast of India. Despite their economic importance and food potential, mangrove clams have received very little attention. Accordingly, a detailed study on the ecology and population dynamic of P. erosa was conducted in the Charao mangrove of Goa, India and some results are discussed here.
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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".