{"id":"W6901454628","doi":"10.6068/dp14ba7f684fc65","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Interprovincial migrants, by age group and sex | Variable: 26 years, In-migrants, Males | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Population; Population statistics; Summary statistics; Demographic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002067374,0.002286467,0.002554455,0.007307456,0.003142637,0.004539881,0.004948148,0.001247777,0.1113638],"category_scores_gemma":[0.01617848,0.001570044,0.001887127,0.03629325,0.0006140437,0.002308257,0.002473412,0.002971586,0.05737256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04636445,"about_ca_system_score_gemma":0.1206478,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945697,"about_ca_topic_score_gemma":0.9923351,"domain_scores_codex":[0.9967005,0.0002533452,0.000376183,0.0004344273,0.001481998,0.0007535979],"domain_scores_gemma":[0.9743367,0.0008825967,0.0006831916,0.0007661558,0.02189787,0.001433501],"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":[0.00002068999,0.00000578372,0.0009544312,0.0002282765,0.00001916583,0.000006946258,0.00002936263,0.0001161078,0.00000893856,0.0003703343,0.9960097,0.002230379],"study_design_scores_gemma":[0.0001699047,0.00001311921,0.023804,0.0009287524,0.0000629018,0.00003251058,0.0005449426,0.000594308,0.0001597252,0.0008050079,0.972794,0.00009076415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005958247,0.00005751287,0.00004450964,0.0001365895,0.00003775655,0.0000242124,0.9983243,0.00008855853,0.001226851],"genre_scores_gemma":[0.001211643,0.0003912599,0.0006927134,0.000201632,0.00002575665,0.0002176836,0.9914343,0.0001887547,0.00563636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1113638,"threshold_uncertainty_score":0.3725489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01518308931823846,"score_gpt":0.2311806910310925,"score_spread":0.2159976017128541,"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."}}