Interrelationship Between Planktonic Diatoms and Selected Governing Physicochemical Parameters of the Hooghly Estuary, Bay of Bengal
Bibliographic record
Abstract
The estuarine ecosystem is generally dynamic and mostly sets the stage for the interplay between phytoplankton such as diatom and the water quality parameters. The study was performed at selected sites of Hooghly estuary to monitor the effect of chosen physicochemical parameters (pH, salinity, dissolved oxygen, nutrients etc.) in relation to seasonal fluctuations in the diatom communities (Chl a and population density). The study encompassed a period of two years (Nov’12 to Oct’14). Seasonal variations in the Redfield ratio (N: P) during the tenure of the study ranged from 5.52 during premonsoon to 14.43 during monsoon. Low salinity and high inorganic compounds (NO 3 , PO 4 and SiO 4 ) levels in the coastal water could have contributed to the predominance of diatoms over dinoflagellates, as observed during the study. The study also reflected the fact that in the mangrove dominated estuarine ecosystems, diatom species like Skeletonema sp., Thalassionema spp., Synedra sp. etc possess potentials to be used as bioindicators to nutrient enriched ecosystem and therefore, can serve as ecological tools to monitor water quality.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".