{"id":"W4401812326","doi":"10.55016/ojs/sppp.v15i1.74699","title":"Population Growth and Population Aging in Alberta Municipalities","year":2022,"lang":"en","type":"article","venue":"The School of Public Policy Publications","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Population growth; Population ageing; Population; Geography; Demography; Sociology","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005051712,0.0001141289,0.0002121522,0.001899741,0.0006398452,0.0003600049,0.0008660901,0.00003968885,0.0002525575],"category_scores_gemma":[0.008828641,0.00008959755,0.00007601066,0.004021196,0.00009283247,0.001055134,0.0003353143,0.0002500054,0.000009361644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009886749,"about_ca_system_score_gemma":0.0001860841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09967136,"about_ca_topic_score_gemma":0.006247126,"domain_scores_codex":[0.9966184,0.000857597,0.0008653165,0.0003318519,0.001030101,0.0002966601],"domain_scores_gemma":[0.9972842,0.001124006,0.0004715257,0.0007589846,0.0002323346,0.000128983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000003508772,0.0000481065,0.3906828,0.000003362621,0.000008822049,3.331923e-8,0.001053949,0.001067858,0.0000238976,0.6031361,0.0005279793,0.003443532],"study_design_scores_gemma":[0.0001948681,0.00001528152,0.7555519,0.000003113843,0.000006723712,0.000005746199,0.002682005,0.009476697,0.000001345168,0.2304065,0.001567278,0.00008854331],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.913096,0.0001159747,0.0004140161,0.07827196,0.00008361755,0.0002563853,0.00004063473,0.00004628023,0.007675215],"genre_scores_gemma":[0.9969763,0.00002842663,0.0001796098,0.0004918761,0.00006203964,0.0001416184,0.0001282537,0.00001204358,0.001979885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3727296,"threshold_uncertainty_score":0.9995204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1303303211388744,"score_gpt":0.3865484457756833,"score_spread":0.2562181246368089,"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."}}