Духовно-нравственные основы марийского язычества в преподавании родной литературы (в связи со сменой парадигмы образования)
Bibliographic record
Abstract
Reductions in atmospheric emissions from the metal smelters in Sudbury, Canada, produced major improvements in acid and metal contamination of local lakes and indirectly increased dissolved organic carbon (DOC) concentrations. Metal toxicity, however, has remained a persistent problem for aquatic biota. Integrating high-throughput, nontargeted mass spectrometry metabolomics with conventional toxicological measures elucidated the mediating effects of dissolved organic matter (DOM) on the toxicity of Cu to Daphnia pulex-pulicaria, a hybrid isolated from these soft water lakes. Two generations of daphniids were exposed to Cu (0-20 μg/L) at increasing levels of natural DOM (0-4 mg DOC/L). Added DOM reduced Cu toxicity monotonically with median lethal concentration values increasing from 2.3 μg/L Cu without DOM to 22.7 μg/L Cu at 4 mg DOC/L. Reproductive output similarly benefited, increasing with DOM, yet falling with increases in Cu. Second generation reproduction was more impaired than the first generation. Dissolved organic matter had a greater influence than Cu on the metabolic status of the daphniids. Putative identification of metabolite peaks indicated that DOM elevation increased the metabolic energy status of the first generation animals, but this benefit was reduced in the second generation, although evidence of increased oxidative stress was detected. These results indicate that Sudbury's terrestrial ecosystems should be managed to increase aquatic DOM supply to enable daphniid colonists to both survive and foster stable populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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; both teacher heads agree on what is shown here.
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".