{"id":"W2313162149","doi":"10.7122/439342-ms","title":"A Chemical CO2 Sensor Monitoring CO2 Movement Under Reservoir Conditions","year":2015,"lang":"en","type":"article","venue":"Carbon Management Technology Conference","topic":"CO2 Sequestration and Geologic Interactions","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Submarine pipeline; Petroleum engineering; Brine; Environmental science; Plume; Enhanced oil recovery; Geology; Produced water; Seawater; Pressure sensor; Fossil fuel; Geotechnical engineering; Waste management; Oceanography; Engineering; Meteorology","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":[0.000204092,0.0004585723,0.0003215671,0.0005933766,0.0003171869,0.0004714167,0.0007976146,0.0006139791,0.001948974],"category_scores_gemma":[0.000676494,0.0002292906,0.0001656886,0.0005442872,0.0002640767,0.0006590682,0.0004641314,0.0003396733,0.0003493731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004600614,"about_ca_system_score_gemma":0.0005323071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002679204,"about_ca_topic_score_gemma":0.003051198,"domain_scores_codex":[0.9993862,0.00004249647,0.00002308097,0.0001601793,0.0003443431,0.00004372294],"domain_scores_gemma":[0.9993623,0.0001144168,0.0001182319,0.00005390732,0.0003009004,0.00005033454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001045291,0.0000298662,0.002430464,0.00006550234,0.000006985737,0.00006529116,0.00002356068,0.0004089013,0.9866095,0.00007537915,0.0002574629,0.0099226],"study_design_scores_gemma":[0.0000138623,0.0003972026,0.01114911,0.000005240659,0.00002105101,0.0002378092,0.00003778139,0.01495523,0.9705505,0.00004041533,0.002561996,0.00002970424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9235482,0.0006199329,0.06602309,0.0002810031,0.0001768071,0.000219681,0.0021839,0.0015105,0.005436816],"genre_scores_gemma":[0.9697824,0.000202876,0.02624827,0.0001164993,0.00001866889,0.00006239484,0.0005110689,0.00002748958,0.003030377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002679204,"threshold_uncertainty_score":0.006519973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03919623958001507,"score_gpt":0.2819607378297024,"score_spread":0.2427644982496873,"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."}}