Composite tracks of Mediterranean cyclones (1979-2020)
Bibliographic record
Abstract
The composite tracks of Mediterranean cyclones have been produced by combining an ensembles of 10 independent track datasets, applied to ERA5 reanalysis for the period 1979-2020. Composite tracks describe more intense and longer-lasting cyclones with more distinguished early, mature and decay stages than cyclones coming from individual tracking methods. Composite tracks are ranked according to their confidence level, i.e. the number of individual cyclone tracking methods that tracked the same cyclone. For each confidence level, we provide a separate file that includes a matrix of eight columns and a number of rows that varies among the datasets. Each row corresponds to a single track point, while the eight columns provide the following information: - Column 1: A cumulatively increasing index that functions as an identifier of unique cyclone tracks. For instance, all information about the track of cyclone #456 are found in all rows starting with the number 456. - Column 2: Longitude of track points - Column 3: Latitude of track points. It is important to note that geographical coordinates are produced using Step 2 of our method and thus may not match the exact location of grid points of ERA5. - Column 4: Year of occurrence - Column 5: Month of occurrence - Column 6: Day of occurrence - Column 7: Hour of occurrence - Column 8: Lowest MSLP value (in hPa) within a 2.5 degrees radius from the geographical coordinates in columns 2 and 3. These values are only meant to function as an approximate reference of intensity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".