{"id":"W6976693622","doi":"10.6068/dp14ba7fdee3356","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 35 years, In-migrants, Both sexes | Units: # Persons, 1972-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-160.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Health and Medical Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Population; Population statistics; Demographic statistics; Summary statistics; Economic statistics; Socioeconomic status; Internal migration","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":[0.001110728,0.0005835624,0.001070406,0.0001210194,0.000406623,0.00007865312,0.0005241475,0.0006582263,0.0004764637],"category_scores_gemma":[0.0001701538,0.0005309378,1.958067e-7,0.0002670485,0.000301418,0.0002086492,0.0004012967,0.001214235,0.000001864358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002443881,"about_ca_system_score_gemma":0.005446287,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999679,"about_ca_topic_score_gemma":0.9999687,"domain_scores_codex":[0.9952082,0.0008828876,0.001043634,0.001113968,0.0007970844,0.0009542092],"domain_scores_gemma":[0.9964294,0.001077028,0.0005593877,0.0009850474,0.00001946522,0.0009296855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000112756,0.00005797048,0.002906871,0.001725283,0.00009972681,0.0001211879,0.00003581666,1.570443e-7,7.188609e-7,0.00005921375,0.9936789,0.00120141],"study_design_scores_gemma":[0.001087587,0.00009490245,0.0004639276,0.000188103,0.0001987912,0.0000181664,0.001078433,0.0006623862,7.748356e-10,5.499207e-7,0.9956892,0.0005179481],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003482448,0.01284504,0.000006214273,0.00001398527,0.0006277011,0.00129269,0.9848522,0.00004963735,0.0002777193],"genre_scores_gemma":[0.0001157187,0.009909618,0.0001350703,0.000923612,0.0002471694,0.00005092264,0.9874701,0.0001030992,0.001044703],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005201899,"threshold_uncertainty_score":0.9997142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717204182282425,"score_gpt":0.2986948883926788,"score_spread":0.2715228465698545,"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."}}