{"id":"W4210488995","doi":"10.1016/j.biortech.2022.126798","title":"Waste surgical masks to fuels via thermochemical co-processing with waste motor oil and biomass","year":2022,"lang":"en","type":"article","venue":"Bioresource Technology","topic":"Healthcare and Environmental Waste Management","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l'Énergie et des Ressources Naturelles; Mitacs","keywords":"Waste management; Motor oil; Cetane number; Waste oil; Biomass (ecology); Diesel fuel; Environmental science; Petroleum; Municipal solid waste; Waste treatment; Co-processing; Pulp and paper industry; Chemistry; Biodiesel; Engineering; Raw material; Organic chemistry; Catalysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001681856,0.0001991485,0.000316388,0.0003341999,0.0002282811,0.00001157047,0.0001781438,0.0001416334,0.0001598932],"category_scores_gemma":[0.000007886666,0.0001632964,0.00003628124,0.0004463415,0.0002795371,0.00001799152,0.0004781349,0.000344386,0.00002365722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001710421,"about_ca_system_score_gemma":0.00002267236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002870731,"about_ca_topic_score_gemma":0.000002239317,"domain_scores_codex":[0.9984796,0.00003682775,0.0002320009,0.0004812101,0.0003267489,0.0004436343],"domain_scores_gemma":[0.9993284,0.00001749438,0.00006226112,0.0003696543,0.0000109559,0.0002112056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001250331,0.0003576325,0.01568051,0.0004117082,0.0001184201,0.001431702,0.0005181743,0.000009729872,0.3172334,0.000113124,0.0008241456,0.6620511],"study_design_scores_gemma":[0.006992839,0.007658278,0.002410405,0.0002618555,0.0002823901,0.004019731,0.02167936,0.0008912199,0.1200571,0.0001285053,0.8344765,0.001141852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816091,0.0007404519,0.00007285247,0.01409683,0.00002282235,0.0002041219,0.00001025172,0.000204706,0.003038836],"genre_scores_gemma":[0.9963672,0.00002373465,0.000638141,0.0008133395,0.00007425468,0.000142555,0.00001880036,0.00004236296,0.001879653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8336523,"threshold_uncertainty_score":0.6659032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01213457875996264,"score_gpt":0.2549142597233985,"score_spread":0.2427796809634358,"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."}}