{"id":"W2297147793","doi":"","title":"Guides: Demographic Information for Business: Ontario Municipalities","year":2013,"lang":"en","type":"libguides","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Point (geometry); Business; Geography; Economic growth; Regional science; Population; Environmental health; Economics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008102823,0.0007373429,0.0005626716,0.003560445,0.004047662,0.003398665,0.001164153,0.000738784,0.2798615],"category_scores_gemma":[0.004329851,0.0009994021,0.0003735705,0.01217654,0.000400882,0.001816506,0.001469351,0.001005374,0.1521577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01690871,"about_ca_system_score_gemma":0.0556358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.926311,"about_ca_topic_score_gemma":0.9733368,"domain_scores_codex":[0.9991422,0.00004190231,0.00006554558,0.00007010232,0.0005349157,0.0001453435],"domain_scores_gemma":[0.9957616,0.0001781309,0.0001923683,0.000149914,0.003086783,0.0006311695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003809827,0.000005611507,0.0004487682,0.00005380365,6.492149e-7,0.00001247587,0.0001729616,0.00002261075,0.00001832827,0.0005886516,0.9859712,0.01270115],"study_design_scores_gemma":[0.000005239381,0.000002074203,0.004122232,0.00006924949,0.00000130917,0.00001235133,0.0002984165,0.00003652054,0.00002500663,0.0001631921,0.9952566,0.000007745652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002257772,0.001415335,0.001212744,0.004586013,0.0005259126,0.0008183241,0.5910698,0.001798376,0.3963158],"genre_scores_gemma":[0.007342358,0.004799913,0.004720774,0.0009945827,0.0001488342,0.0009923581,0.246073,0.00112004,0.7338082],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2798615,"threshold_uncertainty_score":0.9362299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03302745090991297,"score_gpt":0.2802264147726706,"score_spread":0.2471989638627577,"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."}}