Effects of Oil-Spill Bioremediation Strategies on the Survival, Growth and Reproductive Success of the Mystery Snail, <i>Viviparus georgianus</i>
Bibliographic record
Abstract
In situ bioremediation is now being considered as an operational oil-spill countermeasure technology. While the effects of treatment strategies on microbial populations have been studied extensively, information on bioconcentration and effects on survival, growth and reproduction of higher level macrobiota are limited. Mystery snails, Viviparus georgianus, are attractive wetland biomonitors because they are abundant, short-lived, dioecious, ovoviviparous, easy to collect and grow rapidly during summer months feeding on sediment debris. V. georgianus was used as biomonitors in a controlled oil spill experiment at a wetland site along the St. Lawrence River (Ste. Croix, QC) to assess the impact of crude oil and efficacy of bioremediation treatments. Snails were placed at various time intervals in special enclosures deployed within five treatments and control background plots (n=50/treatment/collection time). Treatments consisted of A: oiled control (natural attenuation), B: as A + ammonium nitrate + triple superphosphate + culling of plants, C: as B but plants left intact, D: as C but sodium nitrate instead of ammonium nitrate, and E: as C with no oil treatment. Although snails could survive in the presence of oil for up to two months, fertilizer treatments brought about increased mortality. Generalized tissue damage with edema and hemocytic infiltration was seen consistently in snails from treatment D and reproduction was impaired in all treatments with or without oil. These findings disclose the need to further evaluate bioremediants in oil-spill response operations for appropriate recovery.
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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) | 0.001 | 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".