Seasonal Predictability of Extratropical Cyclone Statistics in the Canadian Seasonal to Interannual Prediction System (CanSIPS)
Bibliographic record
Abstract
Presented by Norman Shippee at the American Meteorological Society's 97th Annual Meeting in January, 2017: CanSIPS reproduces the overall spatial pattern of cyclone track density found in ERA-Interim. Individual models of CanCM3 and CanCM4 over and under-represent the observed storm track, respectively. CanSIPS mean storm track and spread of track density is well represented, though an overall overprediction of storm track density is evident across the North Pacific, particularly from 45 - 60 deg N. This overprediction of storm track density is present in all components of the CanSIPS system. Moderate to strong correlation between CanSIPS mean storm track density and ERA-Interim track density are found across the primary storm track in the North Pacific and in the primary formation regions for Atlantic cyclones affecting North America (Gulf of Mexico and Cape Hatteras) Most CanSIPS bias in the North Pacific is centralized in the exit regions of the Pacific storm track.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".