Discriminant analysis of the freeze-up and break-up conditions in the Inner Mongolia Reach of the Yellow River
Bibliographic record
Abstract
Abstract This study divided the total storage potential in a natural channel into the ice production volume and the water storage capacity volume. Thermal factors, hydraulic processes, topography, and ice formation were selected to derive a discriminant equation for freeze-up and break-up conditions in the Inner Mongolia Reach of the Yellow River. The trends observed from data for the freeze-up dates, break-up dates, and total frozen days from 2017 to 2020 conform to the principle that the river is gradually frozen from the downstream to the upstream and later thawed from the upstream to the downstream. The number of frozen days in the downstream is greater than in the upstream. Results indicate that freeze-up typically occurs when the proportion of ice in the channel is relatively high. Higher temperatures and greater discharges are required to facilitate the break-up of the river when the equilibrium ice thickness is greater. This study can provide a theoretical basis and framework for establishing an accurate freeze-up and break-up forecast model to prevent and mitigate ice-induced disasters.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".