{"id":"W2590630242","doi":"10.25336/p6p59b","title":"Population Change in Canada","year":2017,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Population; Geography; Demographic economics; Demography; Socioeconomics; Economics; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001146145,0.0001055765,0.0002520892,0.0005545647,0.0003835655,0.0001022017,0.0003434308,0.00005186972,0.00002517783],"category_scores_gemma":[0.002059896,0.0000983898,0.00002732787,0.0003324042,0.00003158335,0.0005143738,0.00003931654,0.00009805329,0.000009565409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00144345,"about_ca_system_score_gemma":0.0001976054,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9997653,"about_ca_topic_score_gemma":0.9999961,"domain_scores_codex":[0.9982416,0.00008413343,0.000536712,0.0003236232,0.0005096426,0.0003042925],"domain_scores_gemma":[0.9988703,0.0001288211,0.000245259,0.0005143778,0.0001242669,0.0001169891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002845172,0.000001774557,0.9442319,0.000002747517,0.000002616035,0.00001552419,0.0004733394,0.0006814536,2.093873e-7,0.0008367137,0.0002471579,0.05350376],"study_design_scores_gemma":[0.0001625966,0.000004078787,0.9721597,0.00004191055,0.000002334011,9.276526e-7,0.001264407,0.01463493,1.831551e-7,0.01123114,0.0003909523,0.0001068531],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955085,0.000379044,0.000005120334,0.001415475,0.001245955,0.0001913836,0.00001630879,0.000005674547,0.001232563],"genre_scores_gemma":[0.9993755,0.00006946921,0.00005838788,0.0002844573,0.00007580778,0.00003300211,0.00003215685,0.000007247894,0.00006393859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0533969,"threshold_uncertainty_score":0.401222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4280009991414502,"score_gpt":0.4612786900685084,"score_spread":0.03327769092705818,"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."}}