{"id":"W4400059986","doi":"10.3897/oneeco.9.e122079","title":"A GIS methodology for mapping regional and community vitality for Canada using the CanEcumene 3.0 Geodatabase with census data","year":2024,"lang":"en","type":"article","venue":"One Ecosystem","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Natural Resources Canada","funders":"Canadian Forest Service; Natural Resources Canada; U.S. Forest Service","keywords":"Census; Vitality; Geography; Regional science; Spatial database; Geographic information system; Cartography; Database; Environmental planning; Spatial analysis; Computer science; Remote sensing; Sociology; Demography; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007843733,0.0006572802,0.0004056685,0.008987688,0.001881931,0.002556296,0.001161747,0.0002425862,0.006074107],"category_scores_gemma":[0.00394393,0.0004079618,0.0007307332,0.01798887,0.0004735504,0.0008238091,0.001703353,0.0007201562,0.001061324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01754658,"about_ca_system_score_gemma":0.04428728,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9759758,"about_ca_topic_score_gemma":0.9837602,"domain_scores_codex":[0.9991001,0.00007132567,0.00006108051,0.0001224538,0.0005356412,0.0001094598],"domain_scores_gemma":[0.9984241,0.0001411526,0.000120531,0.00009813636,0.001123363,0.00009276065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001157822,0.0001820632,0.1449328,0.0007260603,0.0002869579,0.0004987011,0.004137505,0.03733112,0.004788876,0.05982123,0.1741866,0.5729922],"study_design_scores_gemma":[0.00007072792,0.00006481531,0.3190355,0.0004866318,0.0001606829,0.0005433403,0.008137528,0.1520408,0.005752945,0.01643704,0.4969805,0.0002894861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1442444,0.001312762,0.4926549,0.001895875,0.0002125444,0.003492145,0.241588,0.01387294,0.1007266],"genre_scores_gemma":[0.2131472,0.0009600331,0.6792684,0.0001262919,0.00001554937,0.001738924,0.08691223,0.0006320427,0.01719932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02402419,"threshold_uncertainty_score":0.1273099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4129444920181378,"score_gpt":0.3918841914562843,"score_spread":0.02106030056185348,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}