{"id":"W6901734987","doi":"10.6068/dp14ba808fdc86","title":"Trend 2000 - 2003. Statistics Canada. CANSIM: Aboriginal People | Country: Canada | Table: Canadian Community Health Survey (CCHS 1.1 and 2.1) off-reserve Aboriginal profile | Variable: No pain or discomfort, Males, Non-Aboriginal | Units: , 2000-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-001.","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; Socioeconomic status; Population; Economic statistics; Population statistics; Summary statistics; Health 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":[0.002613878,0.002214435,0.002722589,0.007594566,0.003370371,0.004701511,0.00538072,0.001496064,0.1184347],"category_scores_gemma":[0.01920038,0.00186703,0.002147368,0.03733876,0.0006583347,0.002409663,0.002380541,0.002947145,0.07377264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04670984,"about_ca_system_score_gemma":0.1281454,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9938129,"about_ca_topic_score_gemma":0.9909726,"domain_scores_codex":[0.9962682,0.0003157335,0.0004585605,0.0005037056,0.001661161,0.0007926321],"domain_scores_gemma":[0.9713606,0.001182594,0.0008627898,0.001187243,0.02387478,0.001532018],"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":[0.00002148157,0.000004812749,0.0006594079,0.0002246519,0.00001718991,0.000005790277,0.000024052,0.00007863943,0.000008113852,0.0003311194,0.9968099,0.001814898],"study_design_scores_gemma":[0.0001499984,0.00001057507,0.01702652,0.0009065599,0.00006288186,0.00002695822,0.0004388344,0.0004100635,0.0001272742,0.0007761061,0.9799784,0.00008581843],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000441482,0.00005061191,0.00003837766,0.0001367473,0.00003668516,0.00002141564,0.998353,0.00009769593,0.001221357],"genre_scores_gemma":[0.0008160676,0.0003207948,0.0007043307,0.0002228609,0.00002170308,0.0002090057,0.9921116,0.0002174726,0.005376237],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1184347,"threshold_uncertainty_score":0.3962038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251007695429118,"score_gpt":0.2848610689822995,"score_spread":0.2597602994393877,"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."}}