{"id":"W1856437313","doi":"10.25336/p6d615","title":"Canadian Provincial Population Growth: Fertility, Migration, and Age Structure Effects","year":2009,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Global Health Care Issues","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Fertility; Age structure; Demography; Immigration; Population; Net migration rate; Total fertility rate; Geography; Population structure; Population growth; Projections of population growth; Demographic analysis; Demographic economics; Research methodology; Economics; Family planning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001696324,0.0005174399,0.0006314152,0.001765746,0.002669767,0.001129178,0.001272845,0.0004849189,0.004882377],"category_scores_gemma":[0.007823806,0.0002078197,0.001192508,0.004161256,0.001111555,0.0006228627,0.001096462,0.0008362465,0.0002401535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04131501,"about_ca_system_score_gemma":0.06870389,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962316,"about_ca_topic_score_gemma":0.996982,"domain_scores_codex":[0.9988047,0.0002154712,0.00003202684,0.0001104914,0.0003776915,0.0004596863],"domain_scores_gemma":[0.9969808,0.0006172464,0.00028745,0.000162686,0.001405699,0.0005459412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003178725,0.0001040338,0.8215045,0.0002204948,0.0003598828,0.0004965033,0.002564584,0.02310534,0.0004751495,0.05472187,0.02272935,0.07340033],"study_design_scores_gemma":[0.00004228175,0.00007709047,0.9309232,0.0001708543,0.0004338942,0.0001785426,0.002641853,0.02346878,0.0004239939,0.00666838,0.03491602,0.00005518667],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8761159,0.0116665,0.004022896,0.01650296,0.0003300378,0.0001650962,0.01172092,0.0002099571,0.07926586],"genre_scores_gemma":[0.9823946,0.004192889,0.001118123,0.0002971402,0.0000452034,0.00002295039,0.001665607,0.00003144524,0.01023198],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04131501,"threshold_uncertainty_score":0.2997627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03719988233463152,"score_gpt":0.4072202399793866,"score_spread":0.370020357644755,"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."}}