{"id":"W6920368868","doi":"10.6068/dp14ba801700e93","title":"Trend 1976 - 2007. Statistics Canada. CANSIM: Government - Balance Sheets | Country: Canada | Table: Balance sheet of federal, provincial and territorial general and local governments | Variable: Liabilities (x 1,000,000), Local government | Units: $CAD, 1976-2007. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-103.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Balance sheet; Economic statistics; Government (linguistics); Official statistics; Census; Balance (ability); Local government; Debt; Politics","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":[0.002006506,0.002246156,0.00226274,0.009530764,0.003511997,0.005347168,0.004425621,0.001432464,0.1179849],"category_scores_gemma":[0.01939926,0.001771969,0.00168837,0.04324369,0.0006620917,0.002717029,0.002191179,0.002883471,0.07370993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06033464,"about_ca_system_score_gemma":0.1452393,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948086,"about_ca_topic_score_gemma":0.9930795,"domain_scores_codex":[0.9955462,0.0002378612,0.000387825,0.0005055821,0.002312601,0.001009926],"domain_scores_gemma":[0.9605902,0.001273346,0.001023346,0.001149261,0.03429831,0.001665471],"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":[0.00001609691,0.000005114534,0.0007498607,0.0001486481,0.00001239179,0.00000540982,0.00001906859,0.00009606362,0.000008383313,0.0004644589,0.9967152,0.001759474],"study_design_scores_gemma":[0.00007607286,0.000007345115,0.01410007,0.0004868493,0.0000330324,0.00001738785,0.0003463564,0.000354257,0.000157717,0.0006228926,0.9837335,0.00006461486],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006025351,0.00005182964,0.00003315329,0.0001339982,0.00003236693,0.00001726914,0.9977393,0.00009282583,0.001838907],"genre_scores_gemma":[0.001111543,0.0003388964,0.0005738225,0.0001651426,0.00002151466,0.0001325939,0.9893745,0.0001994294,0.008082488],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1179849,"threshold_uncertainty_score":0.4377605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133822763213535,"score_gpt":0.2191609643382176,"score_spread":0.2078227367060823,"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."}}