{"id":"W2266923912","doi":"10.3389/fmicb.2015.01538","title":"Microbial Methane Production Associated with Carbon Steel Corrosion in a Nigerian Oil Field","year":2016,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Corrosion Behavior and Inhibition","field":"Materials Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Shell; Alberta Innovates; Shell Global Solutions International; Suncor Energy Incorporated; ConocoPhillips","keywords":"Methane; Archaea; Carbon fibers; Sulfate-reducing bacteria; Methanogen; Chemistry; Environmental chemistry; Methanogenesis; Produced water; Corrosion; Microorganism; Carbon dioxide; Sulfate; Bacteria; Materials science; Biology; Environmental science; Environmental engineering; Organic chemistry; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001503415,0.0003667823,0.000277659,0.0004346209,0.0003692248,0.0005001582,0.0001544614,0.0004435509,0.0002770234],"category_scores_gemma":[0.0001572931,0.0001649251,0.0002015617,0.0003821764,0.0002817669,0.0001961359,0.0002212463,0.0002223468,0.000114399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003986867,"about_ca_system_score_gemma":0.0004185073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007116481,"about_ca_topic_score_gemma":0.0115537,"domain_scores_codex":[0.9998348,0.0000196747,0.00001007307,0.00004201774,0.00004017138,0.0000531491],"domain_scores_gemma":[0.999897,0.00001621315,0.00003424401,0.000003052741,0.00003448624,0.00001509659],"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":[0.0006497813,0.0001145686,0.09879538,0.0003548603,0.0000270946,0.001005282,0.0007896854,0.0003137084,0.8873776,0.00007846568,0.0001268028,0.01036669],"study_design_scores_gemma":[0.00001241725,0.0006626319,0.7681002,0.00009980931,0.00006767439,0.001295488,0.003783926,0.001495507,0.2215474,0.0001640621,0.002737354,0.0000336318],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988997,0.0003476296,0.000165029,0.00004594742,0.000005838897,0.000006007394,0.000188204,0.000003623159,0.0003380166],"genre_scores_gemma":[0.9980589,0.0005851663,0.0006072471,0.00001579333,0.000007013502,0.000007277756,0.0002390563,0.000002489956,0.0004770844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007116481,"threshold_uncertainty_score":0.01415008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00788772615518598,"score_gpt":0.2119392949246071,"score_spread":0.2040515687694211,"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."}}