{"id":"W6976418080","doi":"10.6068/dp14ba7ee8f724","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: 34 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":"History of Computing Technologies","field":"Computer Science","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":[0.002022317,0.00221831,0.002532452,0.007125165,0.003052613,0.004355985,0.00490629,0.001225666,0.1094335],"category_scores_gemma":[0.01672675,0.001528556,0.001855104,0.03480296,0.0006004091,0.002272913,0.002386979,0.002946611,0.05903164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04489544,"about_ca_system_score_gemma":0.1164301,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942138,"about_ca_topic_score_gemma":0.9920946,"domain_scores_codex":[0.9968261,0.0002423665,0.0003568773,0.0004124587,0.001433871,0.0007285127],"domain_scores_gemma":[0.9737979,0.0008962686,0.0006625538,0.0007531312,0.02253781,0.00135231],"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":[0.00001954832,0.000005829327,0.0009570367,0.0002219023,0.00001842278,0.000006705587,0.00002781701,0.0001207475,0.000008408957,0.0003556477,0.996042,0.002215959],"study_design_scores_gemma":[0.0001676318,0.00001317492,0.02423595,0.0009201086,0.00006150285,0.00003275176,0.0005253386,0.0006268441,0.0001574838,0.0008085967,0.9723602,0.00009043542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006300684,0.00005815427,0.00004550538,0.0001401511,0.00003766309,0.0000240151,0.9983274,0.00008999253,0.001214103],"genre_scores_gemma":[0.001244373,0.0004062881,0.0006804225,0.0001974908,0.00002622814,0.0002121919,0.9916145,0.0001882441,0.005430335],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1094335,"threshold_uncertainty_score":0.3660916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005552163086677,"score_gpt":0.2467414730960987,"score_spread":0.2266859514652319,"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."}}