{"id":"W6901667672","doi":"10.6068/dp14ba8cca84396","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: Reclamation and decommissioning, Capital expenditures, Establishments with 100 to 499 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; Natural resource; Capital (architecture); Descriptive statistics; Production (economics)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005731563,0.001074219,0.001026565,0.0001677553,0.000419169,0.000529842,0.0006504061,0.0004628666,0.001564437],"category_scores_gemma":[0.0000995925,0.0009719483,2.181205e-7,0.0001271533,0.0004074919,0.0008334389,0.0008106595,0.0007788679,0.000007957171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006548032,"about_ca_system_score_gemma":0.001957028,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9983703,"about_ca_topic_score_gemma":0.9833094,"domain_scores_codex":[0.9945874,0.0005376347,0.0007981597,0.001710399,0.001555056,0.0008113767],"domain_scores_gemma":[0.9962059,0.0003502526,0.0009385662,0.00156547,0.00002591522,0.0009138631],"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":[0.0004849062,0.0002129319,0.0001385739,0.0002805437,0.0003101453,0.00009516734,0.00002762337,0.0001374529,0.000463371,0.00001473842,0.9976716,0.000162965],"study_design_scores_gemma":[0.001714761,0.0006680185,0.0001229408,0.0000964225,0.0004626049,0.0002036059,0.0009759124,0.0006070952,0.000006531146,1.758997e-7,0.9940866,0.001055374],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000605304,0.002136978,0.00001114697,0.000006219077,0.0003229479,0.001789948,0.9948996,0.00004501468,0.0001828055],"genre_scores_gemma":[0.00197599,0.000684206,0.0003343898,0.00007456233,0.0001186505,0.00006858527,0.9943295,0.0003127328,0.002101413],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01506085,"threshold_uncertainty_score":0.9993483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01580852782900489,"score_gpt":0.2284684494418809,"score_spread":0.212659921612876,"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."}}