{"id":"W6920316420","doi":"10.6068/dp14ba8ea881c53","title":"Trend 2006 - 2010. Statistics Canada. CANSIM: Environment - Pollution and Waste | Country: Canada | Table: Capital and operating expenditures on environmental protection, by type of activity and establishment size | Variable: Pollution abatement and control processes (end-of-pipe), Capital expenditures, Establishments with 500 to 999 employees (x 1,000,000) | Units: $CAD, 2006-2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-087.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Summary statistics; Census; Official statistics; Pollution; Socioeconomic status; Descriptive statistics; Capital (architecture); Natural resource","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":[0.001778461,0.002368909,0.002457596,0.00831147,0.002754755,0.004120365,0.004446518,0.001379311,0.08978901],"category_scores_gemma":[0.01507768,0.001667809,0.002034382,0.03893394,0.0005696944,0.002341604,0.002039528,0.002794536,0.04733369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0535472,"about_ca_system_score_gemma":0.1370064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9947359,"about_ca_topic_score_gemma":0.9931416,"domain_scores_codex":[0.9959992,0.0002230839,0.0004261725,0.0004839175,0.001956992,0.0009107837],"domain_scores_gemma":[0.9694713,0.0009528724,0.001000308,0.0007118909,0.0264253,0.001438389],"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":[0.00002280369,0.000006954866,0.00112386,0.0002547261,0.00002059476,0.000006243756,0.00001717935,0.0001254429,0.00000919517,0.0003696663,0.9963504,0.001692843],"study_design_scores_gemma":[0.0001519469,0.00001430011,0.02808707,0.000810202,0.00007593141,0.00002779216,0.0004165669,0.0005773713,0.0002051541,0.0006110161,0.9689381,0.0000845317],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000649233,0.00005724453,0.00002414438,0.000128808,0.00002896227,0.00001367933,0.9985921,0.00005584487,0.001034216],"genre_scores_gemma":[0.001056078,0.000358911,0.0003997204,0.000176253,0.00001991951,0.000113699,0.9924402,0.0001052589,0.00532997],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08978901,"threshold_uncertainty_score":0.388514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133611906832738,"score_gpt":0.2216258245972818,"score_spread":0.208264633914008,"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."}}