{"id":"W2947521990","doi":"","title":"Labour mobility and interprovincial trade in Canada","year":2019,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Endogeneity; Gravity model of trade; Immigration; Economics; Estimation; Net migration rate; Geography; Demographic economics; International trade; Econometrics; Population; Demography; Population growth","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00198286,0.0003726189,0.00133424,0.0008035156,0.00007265955,0.0001700319,0.0007475691,0.0003902286,0.0001939407],"category_scores_gemma":[0.0002614555,0.0004791286,0.0001992018,0.0001691375,0.0001700119,0.000134177,0.0009968594,0.001653903,0.00001947877],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005002587,"about_ca_system_score_gemma":0.001949256,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.872634,"about_ca_topic_score_gemma":0.9694001,"domain_scores_codex":[0.9959797,0.00009519856,0.001538598,0.001500727,0.00007661765,0.0008091769],"domain_scores_gemma":[0.9980435,0.0003290481,0.0004479656,0.0009357902,0.00002667372,0.0002169856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001373228,0.0002076569,0.8848894,0.0003626821,0.0002009762,0.0000483334,0.0003699777,0.04326462,0.000002914817,0.03439317,0.00008530406,0.03603762],"study_design_scores_gemma":[0.001313605,0.00008733862,0.6646717,0.0001580324,0.000006551728,0.000006499677,0.0006680961,0.2380611,0.000008647662,0.05012166,0.04368106,0.001215678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9573746,0.0006806526,0.000005408045,0.00175124,0.0005517635,0.0006456051,0.0006529724,0.000008118698,0.03832968],"genre_scores_gemma":[0.989957,0.008466082,0.00009140887,0.0002476923,0.0001369315,0.000126823,0.00005971193,0.0000532584,0.0008610775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2202177,"threshold_uncertainty_score":0.9997661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651031802750252,"score_gpt":0.2504506904044012,"score_spread":0.2239403723768986,"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."}}