Bibliographic record
Abstract
In Sothern Manitoba, flooding along the Red and Assiniboine River floodplains causes road closures, crop planting delays and destruction of homes. Agriculture is the dominant land-use in the region and as a result the area has been extensively drained. Studies conducted by Ducks Unlimited have determined that 70% of wetlands were lost between the 1986 and 2005. Wetlands are known for their ability to reduce flooding thus their reintroduction into Southern Manitoba demonstrates a good alternative to engineering solutions. Hanuta reconstructed and mapped land cover information of 100 townships within the Red River drainage basin dating back to 1870, before drainage for agriculture occurred. Hanuta's work will provide a historical reference given that the ultimate goal of this project is to use polarimetric radar data to map historic wetlands in southern Manitoba. This review assesses commonly used hydrological indicators for the detection of historic wetlands and proposes an appropriate methodology for detecting the location of historic wetlands for the study site, using remotely sensed data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".