Pulp and paper environmental effects monitoring in Canada: An overview", Water Quality Research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental effects monitoring (EEM) is a requirement for pulp and paper mills in Canada discharging effluent directly into receiving environments under the Pulp and Paper Effluent Regulations of the Fisheries Act. The objec-tive of the EEM program is to assess effects on fish, fish habitat and the use of fisheries resources by humans, potentially affected by the deposit of mill efflu-ent in aquatic receiving environments. The information provided by the moni-toring program will contribute to assessing the adequacy of the regulations. Difficulties encountered in the first round of monitoring led to an extensive sci-ence review of key components and resulted in improvement to process, scien-tific defensibility of the monitoring data and site-specific flexibility of the EEM program. The second cycle of EEM was, overall, markedly more successful than Cycle 1. However, problems were still evident for fish surveys conducted in marine and estuarine environments. The adoption of improved alternative monitoring approaches (e.g., caged bivalves, mesocosms) should alleviate many of these problems. An overview of the EEM program, results to date, alternative monitoring approaches, and research priorities to fill data gaps are presented.
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.
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 | 0.000 |
| 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) | 0.012 | 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 it