Monitoring Water Quality through the Manitoba Great Lakes Program
Bibliographic record
Abstract
The upper Manitoba Great Lakes (MBGL – Lakes Manitoba, Winnipegosis and Waterhen) act as filters that intercept nutrient flow from the Lake Winnipeg watershed, both as natural nutrient sinks and especially through operation of the Portage Diversion. Sample sites were established on all three lakes to measure physical parameters such as conductivity, temperature, depth, oxygen and light, as well as taking water samples to measure water chemistry and biological samples for algae and zooplankton. Li Gran Lak supirieurre dju Manitoba (MBGL – Lak Manitoba, Winnipegosis pi Waterhen) sa li kom di filte ksa l’anpêsh li nutriman d’kouli dju bassein idrografik varsan dju Lak Winnipeg, kom ein pwi d’nutriman nachurel pi, surtou, par li opirassion dju Kanal di Dirivassion d’Portage. Sa lâ itabli di sitte d’ishanchiyonaj su li twa lak pour misuri li paramêt fizik, kom la kondâkchiviti, la tanprachurre, la prâfondeurre, l’âxijêne pi la limyerre, pi même prande di ishanchiyon d’l’ô pour misuri la shimi d’l’ô pi misuri di ishanchiyon biâlojik pour l’alg pi dju zooplankton.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".