{"id":"W2321220942","doi":"10.1021/ie402239p","title":"Waste Biomass-Extracted Surfactants for Heavy Oil Removal","year":2014,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Extraction (chemistry); Pulmonary surfactant; Biomass (ecology); Chemistry; Compost; Pulp and paper industry; Toluene; Hexane; Asphalt; Green waste; Wastewater; Environmental chemistry; Environmental science; Waste management; Chromatography; Materials science; Organic chemistry; Environmental engineering; Geology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002324052,0.000631451,0.0005029972,0.0005327625,0.0002033476,0.0004281901,0.000230298,0.000390947,0.0006926665],"category_scores_gemma":[0.0001846423,0.0002218655,0.0004408348,0.0004817882,0.0001047596,0.0002681873,0.0003352271,0.0002873786,0.0004315972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002946064,"about_ca_system_score_gemma":0.0004131798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00171596,"about_ca_topic_score_gemma":0.005000758,"domain_scores_codex":[0.9997526,0.00003657198,0.00002456521,0.0000277582,0.0001200535,0.00003847158],"domain_scores_gemma":[0.9999077,0.00001562544,0.00001654372,0.000005711116,0.00003952315,0.00001480292],"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":[0.0000455359,0.00002642183,0.0001546182,0.0000937173,0.000006244642,0.00003100558,0.000008418115,0.0001081973,0.9962066,0.00001642132,0.00001271552,0.003290068],"study_design_scores_gemma":[0.000004102017,0.0001267124,0.0006180942,0.000005347219,0.00001466434,0.00004399922,0.00001469612,0.0004902931,0.9979585,0.000007725436,0.0007133556,0.000002645882],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860504,0.004095924,0.007925472,0.0000760949,0.00003049914,0.0000677736,0.0002006364,0.00009481505,0.001458442],"genre_scores_gemma":[0.9857209,0.002887694,0.007787036,0.0000403931,0.000009211199,0.00003577603,0.0003336395,0.00002164325,0.003163778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00171596,"threshold_uncertainty_score":0.003411949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0631803105303954,"score_gpt":0.2973156332463138,"score_spread":0.2341353227159184,"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."}}