Étude et prévention des accidents de la route impliquant le cerf de Virginie dans l'Ouest-de-la-Montérégie
Bibliographic record
Abstract
Résumé : Problématique très en vue en Amérique du Nord en général, et au Canada en particulier, les collisions entre véhicules et animaux sauvages entrainent chaque année plusieurs centaines de victimes et des milliers de dollars en coûts sociaux. Parmi les espèces animales impliquées dans l'accidentologie faunique, le cerf de Virginie est particulièrement concerné dans la partie sud du Québec. Afin de cibler les facteurs prépondérants et mitiger l'importance de la problématique dans la région à l'étude — l'Ouest-de-la-Montérégie — le mémoire vise à dresser un portrait statistique, à déterminer les sections à fort risque de collision avec le cerf et à proposer des mesures de mitigation pour mieux contrôler l'impact de la problématique dans le contexte ouest-montérégien. Lequel propose un paysage d'une dichotomie remarquable entre la forêt, espace refuge du chevreuil surtout en saison froide, et la plaine où le cheptel sort en quête de nourriture. Au cours de l'étude, l'accent est mis sur la proportion d'espace boisé au sein d'une amplitude clé autour du réseau, et confirme les hypothèses régulièrement indiquées dans la littérature spécialisée, soit d'une part la recrudescence d'évènements accidentologiques lors de saisons particulières associées à la biologie de l'animal, et d'autre part la prépondérance de collisions durant des créneaux horaires quotidiens bien déterminés. Par ailleurs, le flux de circulation, attribut essentiel dans toute analyse de réseau routier, sera questionné grâce à une analyse statistique qui mettra en lumière son influence sur l'importance du phénomène. Finalement, sept portions à fort risque de collision avec le cerf ressortent de la segmentation du réseau à l'étude par le prisme de l'analyse des sections de trafic, et des recommandations sont proposées pour chacune d'entre elles; si un aménagement mitigateur s'avère pertinent pour certaines des portions déterminées, l'aspect prévention doit lui aussi être mis de l'avant notamment à travers des campagnes de sensibilisation.||Abstract : As an important problematic in the North American transportation field, and particularly in Canada, the road accidents involving wild animals lead each year to several hundreds of victims and substantial social costs. Among the wild species involved in this kind of collisions, the Virginia deer concerns the biggest part of the southern Quebec accidental events. In order to know which are the most influential factors and to reduce the impact of the phenomenon in the studied area - Ouest-de-la-Montérégie - the dissertation aims to draw up a statistical portrait, to determine the road sections with a high risk of deer-vehicle collision (DVC) and finally to suggest some countermeasures which can help to control the problematic in the studied geographical context. This territory shows a remarkable dichotomy with, on one hand, forests where the animals can take refuge, specially during winter, and on the other hand plains where the deers can find some food. The study develops the importance given to the part of forest inside a key zone around the road network, and confirms the hypothesis regularly seen in the specialized literature; that is to say that accidents involving deers more often happen during particular biological seasons for the species, and that the same collisions more often occur at a certain time of the day. Furthermore, the circulation flow, which is very important in every network analysis, will be studied in order to know how influential it can be in the problematic. Finally, seven portions with a high risk of DVC result from the segmentation analysis of the road network, thanks to a traffic-section approach. Some recommendations are introduced for each of these sections, and beside the technical countermeasures, prevention and awareness prove to be efficient methods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".