Greater Calgary Metropolitan Region Ecological Connectivity Spatial Products
Bibliographic record
Abstract
The Greater Calgary Region ecological network geodatabase includes a series of products to help integrate ecological connectivity for terrestrial mammals into land use planning. Products include: Ecological_Network: consists of core areas (areas less likely to be developed) and corridors (movement areas for terrestrial mammals) in the Greater Calgary Region. This layer was refined using Overlay_EC_Final, and Core_prioritization layers after discussion with County representative's. Overlay_EC_Final: product that combines terrestrial species connectivity modeling (mule deer, moose, and cougar) and a species agnostic (structural) connectivity model. Results are based on z-score where 0-1 was identified as medium connectivity value and > 1 represents high connectivity value. The medium and high connectivity values were refined and delineated as corridors in the Ecological Network. Core_prioritization: Core areas were defined as areas less likely to be developed (crown not manages by Transportation and Economic Corridors, Parks, municipal ER, private land conservation). To prioritize the core aeras role in the ecological network we ran a confore analysis for three species and then took the average. AVC_cluster_sig: Based on five years (2019-2023) of Alberta Wildlife Watch data provided by Alberta Transportation and Economic Corridors we ran a cluster analysis to identify areas of high risk to motorist safety. See page 18 of technical report. AVC_Corridor_alignment: Highlights areas where there is alignment between AVC clusters (motorist safety) and high ecological connectivity values. See page 20 of technical report.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.096 | 0.022 |
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".