{"id":"W4407641291","doi":"10.1016/j.jhazmat.2025.137654","title":"Machine learning-aided model for predicting oily sludge pyrolysis under various feedstock and operating conditions","year":2025,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of Northern British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Raw material; Pyrolysis; Waste management; Process engineering; Pulp and paper industry; Environmental science; Engineering; Chemistry; Organic chemistry","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":[0.0007971302,0.0006908275,0.0006446394,0.0004581198,0.0003006642,0.0005963169,0.0005437199,0.0009460556,0.001000843],"category_scores_gemma":[0.001338665,0.0004207543,0.0007972023,0.0003103346,0.0001918673,0.0004146903,0.0003381862,0.0006659079,0.0003070233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006327764,"about_ca_system_score_gemma":0.001030807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084089,"about_ca_topic_score_gemma":0.007080303,"domain_scores_codex":[0.9998192,0.00006375196,0.00001138506,0.00004155792,0.00003948055,0.00002461056],"domain_scores_gemma":[0.9994969,0.0003026119,0.00005565977,0.00001862215,0.0001117915,0.00001441434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003067694,0.00002664087,0.0006596079,0.00001702767,0.00001302266,0.00001512482,0.000006016729,0.9944384,0.001065671,0.00009628411,0.0000596962,0.003571722],"study_design_scores_gemma":[0.000001639776,0.000007857274,0.0001000274,8.380469e-7,0.000001961333,0.000001224533,7.343378e-7,0.9995944,0.000225271,0.00003599548,0.00002895232,0.000001223108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5358725,0.0004982736,0.456447,0.0003103541,0.00007387545,0.0001606862,0.0005700365,0.001506113,0.00456122],"genre_scores_gemma":[0.9684425,0.00009280631,0.0293607,0.00004036421,0.000009498663,0.0001341874,0.0002657385,0.00002398083,0.001630258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01084089,"threshold_uncertainty_score":0.0215556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01273864531254281,"score_gpt":0.2526448194813459,"score_spread":0.2399061741688031,"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."}}