A Preliminary Investigation on the Toxicity of Tetracera Alnifolia on Piscicola Geometra in Fish Culture
Bibliographic record
Abstract
The toxicity of varying concentrations of T. alnifolia extract on P. geometra (leeches) was investigated. Aqueous crude extract of roots and stem bark of T. alnifolia plant was obtained and concentrations of 5%, 10%, 15% and 20% of extract were made. Twenty-five juvenile C. gariepinus fish were distributed into five tanks of A-control (0%), B (5%), C (10%), D (15%) and E (20%) of herb extract with two replicates all held in static renewal bioassays. Twenty leeches were introduced into each tank and six hourly observations show that leeches were negatively affected by the herb extract. The extract elicited reduction in swimming activity, caused weakness, paleness and death of the leeches. The concentration- response relationship of P. geometra and T. alnifolia extract shows a mortality of 25%, 40%, 70% and 80% and a median lethal time (LT50) of 42h, 30h, 18h and 12h for 5%, 10%, 15% and 20% at 24h exposure respectively. The resulting sigmoid curve had an arithmetic median lethal (LC50) value of 113mg/l and a logarithmic median lethal (LC50) value of 1.72mg/l. Probit mortality of 4.33, 4.75, 5.52 and 5.84 were observed for 5%, 10%, 15% and 2% concentrations. The herb extract did not have any noticeable effect on the fish. Dissolved oxygen was significantly (P<0.05) higher in control than in treatment tanks. The herb extract had a significant effect (P<0.05) on the rate of mortality of P. geometra at 24h exposure time indicating that T. alnifolia extract may be effective in the control of leeches in fish culture.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".