Analysis of lightning detection network data for selected areas in Canada
Bibliographic record
Abstract
An analysis of Canadian Lightning Detection Network (CLDN) data recorded during years 2004 - 2006 is performed for two selected areas in Canada within a 20-km radius around two tall structures: the CN Tower (CNT, 553 m) in Toronto and the Superstack (SS, 380 m) in Sudbury. The explored lightning characteristics include stroke polarity, lake water or land termination (WT or LT), ground stroke densities Ngs, stroke peak currents (including values of I50%, I95%, I5%), distributions of parameters. The results show noticeable differences between characteristics of lightning terminated to lake water and land. In Toronto area (Ngs≈ 3.24 strokes/(km2·year)), a commonly accepted feature, according to which positive strokes exhibit dominating peak currents in comparison to negative ones, is confirmed only for WT lightning (not close to the CNT), especially in the range of high currents. For LT lightning in the range of current amplitudes close to 50% values, the negative strokes are characterized by larger peaks (by more than 30%) with respect to positive ones. No positive strokes to water were recorded within 5 km near the CNT during the period of analysis. While WT events exhibit a lower Ngsthan LT ones, they show larger peak currents. The Sudbury area, characterized by a lower lightning activity (Ngs≈ 0.91 strokes/(km2·year)), shows the common relation between peak currents of positive and negative polarities (first are dominating). For the SS, the estimated number of upward lightning looks rather low: 0.47 strokes or 0.37 flashes per year. For the CNT, it is about 32 strokes or 14 upward flashes per year. Distributions of Ngsalong the distance from the tall objects, beside the increased levels near object, contain dips next to object (up to 3 - 7 km).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".