Kemampuan Reproduksi Daphnia magna Jantan Hasil Induksi Logam Berat (Cd, Pb) Dan Pestisida Diazinon <br><i>[Reproductive Ability Of Male Daphnia magna Induction Results Of Heavy Metal (Cd, Pb) And Pesticide Diazinon]<i>
Bibliographic record
Abstract
Abstract Daphnia magna is one of the natural food which is used widely in fish hatchery. Generally, Daphnia magna is used widely in larval rearing of fish that are traded in the form of resting eggs called ephipia. Ephipia production can be performed with Daphnia magna culture in conditions that are not optimal, one of which is pollution. If the conditions are not optimal then the parthenogenesis Daphnia magna would produced a male individual. The presence of Daphnia magna males will initiate sexual reproduction, where Daphnia magna males will perform on the female and copulation produce ephipia. Ephipia production is influenced by the efficiency of matting, reproduction ephipia will improve if a high mating eficiency of Daphnia magna. Mating eficiency describes the number of females that successflly fertilized by the male.The purpose of this study is to determine the reproductive capacity of Daphnia magna male’s induction of heavy metals (Cd, Pb) and the Pesticide Diazinon on mating efficiency and quality ephipia produced. The research method used is an experimental method by using completely randomized design with 4 treatments and 5 replications so that was followed by Duncan Multiple Range Test. This study uses the ratio of male to female sex 1:30 for each treatment. The treatments in this study consist of control males mated with females, male induced lead (Pb) were mated with female, males induced cadmium (Cd) were mated with females, the male mated with the induction of pesticide Diazinon female. Results showed that treatments using natural male produced an average value of mates which were the highest efficiency and quality ephipia optimal, with precentage of 88,66 and 88,71. So that in order to produce ephipia in large quantities and quality needed natural male culture can be done in the unpolluted waters.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".