{"id":"W2950908114","doi":"10.3389/fmicb.2019.01243","title":"Microbially Enhanced Oil Recovery by Alkylbenzene-Oxidizing Nitrate-Reducing Bacteria","year":2019,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biopterre; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Shell; Alberta Innovates; Shell Global Solutions International; Suncor Energy Incorporated; ConocoPhillips","keywords":"Ethylbenzene; Toluene; Nitrate; Chemistry; Environmental chemistry; Residual oil; Biomass (ecology); Chromatography; Organic chemistry; Biology; Agronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002871992,0.0006452454,0.0005015121,0.0001609215,0.0001018949,0.0004051232,0.0002580312,0.0002778863,0.0004102084],"category_scores_gemma":[0.0002579654,0.0001491739,0.0004272,0.0001769075,0.0001434588,0.0002263612,0.0005410343,0.0003830819,0.0002166219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002618136,"about_ca_system_score_gemma":0.0003414176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001845894,"about_ca_topic_score_gemma":0.0029057,"domain_scores_codex":[0.9996408,0.00006310742,0.00003656015,0.00006559068,0.0001102539,0.00008365863],"domain_scores_gemma":[0.9998719,0.00002552647,0.00003002176,0.00001336979,0.00003302967,0.00002616902],"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":[0.00003620291,0.00002197806,0.0001410442,0.00001931938,0.000002282358,0.00001131574,0.000006535703,0.00002284334,0.9991572,0.000006274789,0.000003229104,0.0005717659],"study_design_scores_gemma":[0.000007248072,0.0003017803,0.002543678,0.000004886093,0.00001162223,0.00004436444,0.00002532269,0.0005782446,0.9961821,0.00001109098,0.000285734,0.000003845466],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975435,0.0002813498,0.001589011,0.0000462257,0.00001519178,0.00002311681,0.00009241248,0.00003061825,0.0003784305],"genre_scores_gemma":[0.9896083,0.000499135,0.007532618,0.00004351862,0.000009193656,0.00004201485,0.0003396522,0.00002147696,0.001904083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001845894,"threshold_uncertainty_score":0.003670275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003047559608455137,"score_gpt":0.1774374959551697,"score_spread":0.1743899363467146,"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."}}