The Application of Fred Sanders' Teaching to Current Research on Extreme Cold-Season Precipitation Events in the Saint Lawrence River Valley Region
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Bibliographic record
Abstract
Abstract Fred Sanders' teaching and research contributions in the area of quasigeostrophic theory are highlighted in this paper. The application of these contributions is made to the topic of extreme cold-season precipitation events in the Saint Lawrence valley in the northeastern United States and southern Quebec. This research focuses on analyses of Saint Lawrence valley heavy precipitation events. Synoptic- and planetary-scale circulation anomaly precursors are typically identified several days prior to these events. These precursors include transient upper-level troughs, strong moisture transports into the region, and anomalously large precipitable water amounts. The physical insight of Fred Sanders' work is used in the analysis of these composite results. Further details of this insight are provided in analyses of one case of heavy precipitation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it