{"id":"W7039221108","doi":"","title":"“The lights are on, but is anyone home?”: Estimating dwelling distribution in rural Alberta","year":2020,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Flood Risk Assessment and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flood myth; Estimation; Distribution (mathematics); Flooding (psychology); Population; Natural disaster; Census; Spatial distribution","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":[0.0004051338,0.0004779725,0.0002583899,0.00101521,0.0006132658,0.0008055327,0.001229743,0.0003858912,0.001080286],"category_scores_gemma":[0.001002717,0.0002341896,0.0003915564,0.001260219,0.0003311972,0.0003137091,0.0005109359,0.0002774669,0.0002133694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006661686,"about_ca_system_score_gemma":0.003634576,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.934646,"about_ca_topic_score_gemma":0.9589838,"domain_scores_codex":[0.9998825,0.00001935944,0.000003882162,0.00003408664,0.00003041209,0.00002976383],"domain_scores_gemma":[0.9997417,0.00008941939,0.00002412522,0.00001749093,0.00009214848,0.00003516083],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002450275,0.0001779268,0.4250768,0.00006544941,0.0001057571,0.0003813453,0.0007164399,0.5227367,0.001557985,0.001459333,0.002379699,0.04509751],"study_design_scores_gemma":[0.00001367251,0.00003218095,0.1276535,0.00002250985,0.00002394333,0.00006032059,0.001202887,0.8683209,0.0003070199,0.0006742408,0.001660961,0.00002788867],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9891927,0.0001478056,0.006959646,0.0001424095,0.000004484009,0.00004716278,0.001772534,0.000145281,0.001588004],"genre_scores_gemma":[0.9883617,0.0001549678,0.007288628,0.00002322497,0.000003009054,0.00001689575,0.002290257,0.00001883082,0.001842333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06535399,"threshold_uncertainty_score":0.1314777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006662522495723256,"score_gpt":0.194300354738315,"score_spread":0.1876378322425918,"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."}}