Bibliographic record
Abstract
ContentsSection 1: River and watershed managementRivers and river basin management issues and concerns in the Pacific Northwest, USA Sustainable management of water resources in the Yellow River basin: the main issues and legal approaches Understanding the consequences of land use changes on sustainable river basin management in the Pacific Northwest, USA Flood flow at the confluence of compound river channelsSection 2: Flood risk managementAssessment of flood vulnerability in the Bodva catchment using multicriteria analysis and geographical information systems Short term assessment and mitigation of flood risks at river basin level Spatial and temporal variation in flooding of rural floodplain farming areas in the Okavango Delta, Botswana Rechecking the characteristic flood levels of a built reservoir after extending the hydrologic time series The importance of law in flood risk management A simplified method for flood risk assessmentSection 3: Erosion and sediment transportIntake systems in ephemeral rivers The relationship between drainage density and soil erosion rate: a study of five watersheds in Ardebil Province, IranSection 4: Water resources managementALICE: an effective tool for groundwater-level regulation for large vine growing areas Forecasting of monthly rainfall in the Murray Darling Basin, Australia: Miles as a case study Water managers' perspectives on reservoir operations for sustainable irrigation in Alberta Section 5: Water qualityDeclining populations of mountain yellow-legged frogs: a reassessment of the evidence implicating pesticides Aquatic ecosystem services of reservoirs in semi-arid areas: sustainability and reservoir management Refinement and application of a coupled tidal prism model with HSPF for managing bacterial water quality impairment in a coastal watershedSection 6: River basin risk analysisA shared water risk assessment for a vulnerable river basin: River Rwizi in Uganda Hydrology of Arctic riversSection 7: Extreme event managementDrought analysis in Slovakia: regionalization, frequency analysis and precipitation thresholds Drought assessment based on the number of days without precipitation Effect of plan layout on the sediment control efficiency of slit-check dams for stony type debris flows mitigation Investigation of crack development in concrete dams due to water level fluctuation during earthquakes
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.191 | 0.044 |
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".