Network global navigation satellite system survey to harmonize water-surface elevation data for the Rainy River Basin
Bibliographic record
Abstract
Offsets were applied to water-level data from surveyed streamgages to further evaluate the accuracy and utility of updated reference mark elevations presented in this report.Daily mean water levels from active streamgages surveyed in this study were converted to water-surface elevations referenced to the Canadian Geodetic Vertical Datum of 2013.Graphical comparisons of water-surface elevations for streamgages in Namakan Reservoir, Rainy Lake, and selected rivers are presented (referencing the Canadian Geodetic Vertical Datum of 2013).Offsets presented in this report can be used in the evaluation of rule curves and in flood damage curves that fully assess the benefits of one regulation approach over another.In addition, offsets may be used to calibrate hydraulic models developed for four narrows that connect lakes of Namakan Reservoir, refine digital elevation models, and support modeling studies designed to assess the effects of rule curves on aquatic vegetation, benthic invertebrates, northern pike, and walleye.Inset 1 EXPLANATION Active streamgage with map number (table 1) Discontinued streamgage with map number (table 1) 1 16
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.016 |
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".