Proceedings of a workshop on the fluvial transport of sediment-associated nutrients and contaminants held in Kitchener, Ontario, October 20-27, 1976
Bibliographic record
Abstract
The PLUARG, in its Study Plan of 1974 established a series of pilot watershed studies and other special land use studies in the United States and Canada to assess the impact of land use on water quality as related to river loadings to the Great Lakes. It was recognized that a variety of nutrients and contaminants are transported both by mineral and organic sediment. A better understanding of sediment-associated nutrient and contaminant transport in streams in time and space was needed to assess their impact on the Great Lakes. The PLUARG therefore referred this matter to the Research Advisory Board as the IJC's principal advisor on Great Lakes research. An evaluation was requested of the state-of-the-art of this topic together with recommendations for further research. The Board in turn decided to sponsor this workshop to synthesize current research and to identify research needs on nutrient and contaminant transport by sediment within fluvial systems. Clarification was sought on the interrelationships of source, in-channel storage, resuspension and transport mechanisms with long-term, seasonal and single-event flows, and including an examination of the interaction of sediment and water chemistry on key nutrients and contaminants.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.008 |
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".