Characteristics of lightning at and in the vicinity of the CN Tower
Bibliographic record
Abstract
The CN Tower has been the center of tourism in Toronto since it first opened to the public on June 26, 1976. It is the world's tallest manmade freestanding structure as well as Canada's most recognizable icon standing at a height of 553 meters. However, like everything else, there could be a down to this incredible structure. Does it attract more lightning; potentially putting the surrounding area in its vicinity in harm's way, or does it provide lightning protection to this area? Although, extensive analysis have been performed concerning the characteristics of lightning strikes to the CN Tower, not much attention has been given to the characteristics of lightning strikes in the vicinity of the tower or the influence the tower has on the lightning environment around it. This thesis is believed to be the first to fill such a gap and tries to answer these questions. Using the 2005 North American Lightning Detection Network data for the area of up to 100 km from the tower, an extensive investigation of lightning activities in the vicinity of the tower is presented here. A comparison between the characteristics of CN Tower strikes and the characteristics of strikes occurring in its vicinity is also presented. Furthermore, the parameters of the lightning electromagnetic pulse (LEMP) generated by a strike to the tower are compared with those generated by a non-eN Tower strike. A substantial increase in the CN Tower LEMP peak in comparison with that resulting from non-CN Tower LEMP has been found. Therefore, electronic and communication systems located in the vicinity of a very tall structure must be specially protected from the lightning-generated electromagnetic pulse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".