{"id":"W6957715141","doi":"10.6068/dp14ba87c545f12","title":"Trend 1999 - 2011. Statistics Canada. CANSIM: Government - Government Business Enterprises | Country: Canada | Table: Balance sheet and income statement of federal government business enterprises, by North American Industry Classification System (NAICS), end of fiscal year closest to December 31 | Variable: Depreciation, depletion and amortization expense, Goods industries | Units: $CAD x 1,000, 1999-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-105.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Spatial Neglect and Hemispheric Dysfunction","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Economic statistics; Balance sheet; Income statement; Official statistics; Census; Goods and services; Payroll; Business 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002727629,0.0006266633,0.0008777979,0.00003517393,0.0001600729,0.0001819064,0.0007565059,0.0003072868,0.0004550475],"category_scores_gemma":[0.0002173475,0.0006269675,3.70224e-7,0.00042424,0.0002598516,0.000341561,0.0005601165,0.0004374163,0.000002987253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449651,"about_ca_system_score_gemma":0.002784829,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9927114,"about_ca_topic_score_gemma":0.9773788,"domain_scores_codex":[0.9942589,0.0002934959,0.001207077,0.001133355,0.002597139,0.0005100752],"domain_scores_gemma":[0.9960714,0.000397534,0.001813579,0.001211637,0.0001091442,0.0003967127],"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":[0.0003738071,0.0001550507,0.01577247,0.0006330938,0.0001032157,0.0000232843,0.000006357745,0.00008992543,0.0001572338,0.00003613687,0.9822208,0.000428679],"study_design_scores_gemma":[0.0008322736,0.0001424117,0.004395431,0.0001025093,0.0002374436,0.00002618642,0.0004572922,0.001671318,0.000008400061,3.712583e-8,0.9915589,0.0005678154],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004345574,0.0002389234,0.0003315769,0.00001016193,0.0005878397,0.0009134103,0.9968057,0.0000356221,0.0006422506],"genre_scores_gemma":[0.01419641,0.0008815646,0.0001058913,0.0001524613,0.0001187948,0.00005774112,0.983757,0.0001203912,0.0006097235],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01533261,"threshold_uncertainty_score":0.9996182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0156911661649333,"score_gpt":0.2247507442686416,"score_spread":0.2090595781037083,"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."}}