{"id":"W6938983959","doi":"10.6068/dp14ba86ab22667","title":"Trend 1990 - 2008. Statistics Canada. CANSIM: Environment - Pollution and Waste | Country: Canada | Table: Direct plus indirect greenhouse gas emissions intensity, by industry | Variable: Repair and maintenance, Tonnes per thousand current dollars of production | Units: , 1990-2008. 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; Official statistics; Summary statistics; Census; Production (economics); Greenhouse gas; Pollution; Statistical analysis","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":[0.002017247,0.00237211,0.002557892,0.008207776,0.002872923,0.004556079,0.004930852,0.001553771,0.09141715],"category_scores_gemma":[0.01660628,0.001822427,0.002257671,0.04190905,0.0006864449,0.002789751,0.002320652,0.003286814,0.05726519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05732543,"about_ca_system_score_gemma":0.1532752,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9939307,"about_ca_topic_score_gemma":0.9911,"domain_scores_codex":[0.9956529,0.0002607765,0.0004656939,0.0005136391,0.002120706,0.0009862552],"domain_scores_gemma":[0.9659028,0.001056343,0.0009931263,0.0008786729,0.0297428,0.001426268],"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":[0.00001981224,0.000005395537,0.0007779235,0.0002761248,0.00001917668,0.000006018205,0.00001737784,0.0001073838,0.000009400191,0.0003659688,0.9969319,0.001463549],"study_design_scores_gemma":[0.0001339465,0.0000104741,0.01788845,0.0008429423,0.00006683814,0.00002394188,0.0003599649,0.0003931238,0.0001770424,0.0006612482,0.9793674,0.00007464139],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004161442,0.00005293074,0.00002562096,0.0001393354,0.00002943841,0.00001472341,0.9986115,0.00006443953,0.001020508],"genre_scores_gemma":[0.0008950129,0.0003837905,0.0004798269,0.0002023908,0.00001966013,0.0001483462,0.9930283,0.0001469287,0.004695717],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09141715,"threshold_uncertainty_score":0.4159271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0211542561357213,"score_gpt":0.2340468389260896,"score_spread":0.2128925827903683,"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."}}