{"id":"W6945471796","doi":"10.25318/2510005601-eng","title":"Canadian pipeline transport of oil and other liquid petroleum products, monthly","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Petroleum; Pipeline transport; Pipeline (software); Crude oil; Petroleum product; Oil refinery; Pigging","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":[0.0007831664,0.002303206,0.001465094,0.008876774,0.001996737,0.002718428,0.003087578,0.001081248,0.03821612],"category_scores_gemma":[0.006820233,0.0009951944,0.001602286,0.02692294,0.0004812459,0.001314449,0.001306209,0.001828357,0.01613664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02665057,"about_ca_system_score_gemma":0.05811048,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.991867,"about_ca_topic_score_gemma":0.9914014,"domain_scores_codex":[0.9982702,0.00005686658,0.0001676481,0.0002615908,0.0008247942,0.0004188509],"domain_scores_gemma":[0.9943886,0.0002113928,0.0004345862,0.0001942787,0.004395204,0.0003758729],"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":[0.00004967602,0.00001209273,0.003894892,0.000564088,0.00005511186,0.00002226464,0.00003034761,0.0004357589,0.00002857124,0.0007899019,0.9916014,0.002515927],"study_design_scores_gemma":[0.0002061704,0.0000217605,0.08905745,0.0007899427,0.0001302198,0.00008590004,0.0003686952,0.001076249,0.0004004104,0.0005041911,0.9072681,0.00009096383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002331528,0.00009581447,0.00002067565,0.00006345724,0.00001612591,0.000007999557,0.9984589,0.00004603436,0.001057811],"genre_scores_gemma":[0.002683047,0.0004716896,0.0002428586,0.00007992452,0.00001208731,0.00004769576,0.9922487,0.00004099744,0.00417304],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03821612,"threshold_uncertainty_score":0.1933643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006774431853763188,"score_gpt":0.2368568447772704,"score_spread":0.2300824129235072,"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."}}