Ecological Assessment and Molecular Characterization of Spirulina in Freshwater Reservoirs of Kohat, Pakistan
Bibliographic record
Abstract
This pioneering study uniquely identifies and characterizes the presence of algal species, mainly Spirulina, from water reservoirs in the Kohat district of Pakistan, a previously unstudied region for microalgae dynamics. Conducted over one year, from July 2022 to June 2023, the study examined 156 samples from 26 freshwater bodies in Kohat. Only one sample from Usterzai (pH 8.6 ± 0.08, TDSs 313 ± 0.81 mg/L, DO 4.50 ± 0.05 mg/L, EC 540 ± 0.81 µS/cm) contained Spirulina sp., highlighting its rarity and specific environmental preferences. The other 155 samples, with varying parameters, contained different microalgae. Microscopic analysis further confirmed the presence of Spirulina in only one sample. The morphological and molecular analyses of the isolated Spirulina culture showed variability within the population, with phylogenetic analysis illuminating closer relationship with Arthrospira platensis. While multivariate analyses identified key environmental parameters influencing algal species distribution, the selective presence of Spirulina was found less relevant, which requires further investigation in terms of nutrient availability, microbial interactions, or subtle variations in water chemistry for ecological preferences and adaptations.
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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 | 0.001 | 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) | 0.001 | 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".