{"id":"W6920294129","doi":"10.6068/dp14ba7ee88321","title":"Trend 1971 - 2013. Statistics Canada. CANSIM: Population and Demography - Mobility and Migration | Country: Canada | Table: Number of non-permanent residents, by age group and sex for July 1 | Variable: 12 years, Males | Units: # Persons, 1971-2013. 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; Population; Official statistics; Population statistics; Summary statistics; Demographic statistics; Socioeconomic status; Economic statistics; Social statistics","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":[0.002021505,0.002217012,0.002532741,0.00710449,0.003051171,0.004343947,0.004905373,0.001217616,0.1092703],"category_scores_gemma":[0.01669207,0.001521651,0.001854829,0.03483966,0.0006009767,0.002273065,0.002379403,0.002952364,0.05869831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04483489,"about_ca_system_score_gemma":0.1166834,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942592,"about_ca_topic_score_gemma":0.9921501,"domain_scores_codex":[0.9968293,0.0002428273,0.0003563903,0.0004124278,0.001431765,0.000727248],"domain_scores_gemma":[0.9739215,0.0008913933,0.0006584573,0.0007489813,0.02243271,0.001347019],"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":[0.00001955359,0.000005849037,0.0009586728,0.0002230675,0.00001851146,0.000006751001,0.00002803733,0.0001210053,0.000008402139,0.0003590189,0.9960132,0.002238],"study_design_scores_gemma":[0.0001667772,0.00001317054,0.02419049,0.0009223568,0.0000615415,0.00003290314,0.0005278537,0.0006271865,0.0001569384,0.0008143226,0.972396,0.00009041038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006327836,0.00005868437,0.00004608017,0.0001406761,0.00003786921,0.00002418315,0.9983189,0.00009014259,0.00122018],"genre_scores_gemma":[0.00125793,0.0004110608,0.0006900401,0.0001986861,0.00002636147,0.0002141512,0.991546,0.0001889975,0.005466775],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1092703,"threshold_uncertainty_score":0.3655457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02155367779723453,"score_gpt":0.258455187565661,"score_spread":0.2369015097684265,"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."}}