Field Data Report Lake Ontario Tributaries 2005-2006
Bibliographic record
Abstract
The Lakewide Management Plan for Lake Ontario has identified six critical pollutants which contribute to lakewide beneficial use impairments due to their toxicity, persistence in the environment, and/or their ability to bioaccumulate. The six critical pollutants are polychlorinated biphenyls (PCBs), mercury, DDT, dieldrin, mirex, and dioxins. Approximately 80% of the surface water flow to Lake Ontario is from the Niagara River. A long term monitoring program conducted by Environment Canada, as a component of the Niagara River Toxics Management Plan, has provided good estimated loadings of pollutants from the Niagara River and the upstream Great Lakes. However, definitive current information regarding loadings from other U.S. tributaries to Lake Ontario had been lacking. In 2002, the U.S. Environmental Protection Agency (EPA) initiated a program to regularly monitor U.S. tributaries for the critical pollutants. Previous reports have provided program results for 2002 through 2004. This report adds changes and results from 2005 through 2006.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.043 | 0.014 |
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".