RA2 P4 TECHNICAL REPORT
Bibliographic record
Abstract
Understanding the impact of ballast water treatment and neutralization methods on receiving waters is critical to minimizing harmful effects of ballast discharge to the environment, specifically the freshwater of Lake Superior and surrounding Laurentian Great Lakes. While studies have been conducted to evaluate the effect of active substances and disinfection byproducts (DBP) produced by different Ballast Water Management Systems (BWMS) on marine waters, very little has been done to determine what impact these treatment systems could have on a highly utilized Great Lakes port like the Duluth-Superior Harbor, with its seasonally fluctuating organic carbon content and low percent transmittance. Throughout this project, the focus was on a BWMS that utilizes UV radiation combined with filtration as the primary treatment. A series of samples were collected at the Montreal Pier Ballast Treatment System Testing Facility, Superior, WI, during the evaluation of Great Lakes-compatible treatment systems. DBP concentrations and whole effluent toxicity tests were conducted to determine the toxicity of treated discharge water to living aquatic organisms representing three levels of the food web (plants, invertebrates, and vertebrates).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.439 | 0.383 |
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; the direct Gemma label and the distilled Codex classifier 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".