{"id":"W2062283927","doi":"10.1016/j.egypro.2014.11.271","title":"CO2 Pipeline Infrastructure – Lessons Learnt","year":2014,"lang":"en","type":"article","venue":"Energy Procedia","topic":"CO2 Sequestration and Geologic Interactions","field":"Environmental Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"SNC-Lavalin (Canada)","funders":"","keywords":"Pipeline (software); Pipeline transport; Variety (cybernetics); Identification (biology); Set (abstract data type); Computer science; Engineering; Database; Data science; Operating system; Environmental engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003815784,0.0009393463,0.0003244448,0.0009388063,0.000990032,0.003775069,0.002925253,0.002923186,0.02563224],"category_scores_gemma":[0.006980184,0.0002751957,0.0006541437,0.001449162,0.0007927676,0.007084344,0.002083905,0.003354961,0.006262295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003143465,"about_ca_system_score_gemma":0.008894235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0310428,"about_ca_topic_score_gemma":0.04717804,"domain_scores_codex":[0.998531,0.000348858,0.00005088968,0.0001449159,0.0005239632,0.0004003073],"domain_scores_gemma":[0.9961457,0.000833447,0.0001107255,0.0003327564,0.001597187,0.0009802142],"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":[0.0001258228,0.0003945878,0.0042423,0.001212171,0.00002936759,0.0008603988,0.0005779552,0.01244505,0.0005660603,0.03980854,0.5210634,0.4186742],"study_design_scores_gemma":[0.00005130432,0.0003420355,0.004392799,0.0026099,0.00003373854,0.0004145187,0.006448033,0.007450497,0.003214133,0.0538859,0.9210724,0.00008480671],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.0413449,0.02352192,0.03563312,0.5591019,0.0113081,0.0004988331,0.007694163,0.00325819,0.3176388],"genre_scores_gemma":[0.6121066,0.1001781,0.06465326,0.0380353,0.003643617,0.0004691176,0.01024025,0.001021723,0.1696522],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.0310428,"threshold_uncertainty_score":0.08574837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00620630610717503,"score_gpt":0.2278386001046719,"score_spread":0.2216322939974968,"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."}}