Environmental parameters and nutrient concentrations of marine water, Matla River and Thakuran River of Maipith coastal areas in the Indian Sundarban mangroves areas
Bibliographic record
Abstract
Physiochemical parameters (salinity and pH) of the each 18 collected samples were measured using the Eureka 2 Manta multiprobe (Eureka Environmental Engineering, Texas, USA) at ZMT. The inorganic nutrient that includes the combined nitrate and nitrite (NOx), phosphate (PO4), silicate (Si), total organic carbon (TOC) and total nitrogen (TN) were analyzed in this investigation. Total 50mL of each sample was filtered through a 0.7μm syringe filter and poisoned with 200μL of a 3.5 g/100mL HgCl2 solution for further analysis using a continuous flow analyzer (Flowsys by Unity Scientific, Brookfield, USA). For measurements of total organic carbon (TOC), 30mL samples were filtered through 0.45μm pore GF/F filters (Whatman GF/F, GE Healthcare, Pittsburgh, USA) followed by acidification with concentrated HCl (pH below 2) and analyzed by high-temperature oxic combustion (HTOC) method using a TOC-VCPH TOC analyzer (Shimadzu, Mandel, Canada). Seawater standards (Hansell laboratory, RSMAS University Miami, USA) for calibration and quality control artificial and ultrapure water as blanks were used.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".