{"id":"W4229334755","doi":"10.1177/01600176221092483","title":"A Multi-Scale Suitability Analysis of Home-Improvement Retail-Store Site Selection for Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"International Regional Science Review","topic":"Urban and Freight Transport Logistics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Mitacs","keywords":"Metropolitan area; Revenue; Census; Scale (ratio); Geography; Economies of agglomeration; Site selection; Competition (biology); Business; Transport engineering; Computer science; Cartography; Population; Ecology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005150028,0.00009095438,0.0002282344,0.0001380425,0.0001161976,0.000008955252,0.0003614008,0.00001156835,0.000787659],"category_scores_gemma":[0.00003054648,0.00008709306,0.000148659,0.0008813761,0.00008900953,0.00008543194,0.00003144767,0.0001025714,4.852267e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001985354,"about_ca_system_score_gemma":0.0005940054,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2832016,"about_ca_topic_score_gemma":0.8935984,"domain_scores_codex":[0.9985188,0.000008912286,0.0003330897,0.0002260733,0.0007467487,0.0001664151],"domain_scores_gemma":[0.9994332,0.00004461795,0.00008191712,0.0001308337,0.0002405405,0.00006888108],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009566517,0.0007245694,0.6920307,0.002356941,0.002365971,0.00001140531,0.0009313724,0.2192381,0.01863568,0.00891409,0.0267874,0.02790818],"study_design_scores_gemma":[0.0003448466,0.0000978898,0.2136173,0.000150949,0.0006344664,0.0000081132,0.00003677116,0.2996361,0.0001996147,0.0001272575,0.4847803,0.0003663481],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8385282,0.02456928,0.1160309,0.004547841,0.004847488,0.003656314,0.003074271,0.00025797,0.004487698],"genre_scores_gemma":[0.9954532,0.0008088462,0.002492366,0.000329766,0.00002382795,0.0001403415,0.0002056079,0.000007405824,0.0005386598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6103969,"threshold_uncertainty_score":0.8624313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03854305384229825,"score_gpt":0.2500485405628704,"score_spread":0.2115054867205722,"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."}}