Mussel reefs in sub-littoral zone-An important habitat for infaunal and ichthyofaunal diversity
Bibliographic record
Abstract
A Sub-littoral mussel reefs harbours rich and diverse invertebrate communities. They \nutilize the reef complex as their habitat, rich feeding substrate and also as refuge from \npredation. Though the invertebrate diversity of the reefs is available, reports pertaining \nto their relation to dietary habit of reef fishes are lacking. A study was taken up at the \nsub-littoral mussel reefs occurring off Someshwara Coast (120 47’ 19” N 740 51’ 05”E) \nin Karnataka (eastern Arabian Sea) to ascertain the diversity reef as well as the fish \nfauna of the region. The invertebrate community of the reef was collected by quadrant \nsampling method. The details on fish fauna of the reefs were collected by visual census \nand also by using semi-structured interviews with local fishers. Detailed study was \ncarried out to find the dietary relationship of the ichthyofauna with the diverse \norganism associated with the sub littoral mussel beds. Apart from barnacles and \nmussels, the invertebrate community was dominated by polychaetes followed by \namphipods and crablets. The major ichthyofaunal diversity includes fishes of the family \nLeiognathidae, Lutjanidae, Siganidae, Sciaenidae, Epinephelidae, Carangidae, Ariidae, \nHaemulidae, Cynoglossidae, and others. The information pertaining to the dietary \nhabits of the fish assemblages were compared with the in-faunal and ichthyofaunal \ndiversity of the reefs to bring out the importance of mussel bed habitat.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".