{"id":"W4388838881","doi":"10.1016/j.apenergy.2023.122321","title":"Machine learning assisted techno-economic and life cycle assessment of organic solid waste upgrading under natural gas","year":2023,"lang":"en","type":"article","venue":"Applied Energy","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Kara Technologies; Alberta Innovates; Alberta Innovates Bio Solutions","keywords":"Life-cycle assessment; Renewable energy; Biomass (ecology); Natural gas; Process simulation; Engineering; Waste management; Process engineering; Process (computing); Environmental science; Municipal solid waste; Computer science; Economics; Production (economics)","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":[0.0005789875,0.0003752722,0.000345575,0.0008700519,0.0002692344,0.0005352966,0.0002820997,0.0005200603,0.0006332941],"category_scores_gemma":[0.000601475,0.0001289386,0.0004557445,0.0004924505,0.0001695413,0.0004058484,0.0001981351,0.0002954454,0.0001145559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008390373,"about_ca_system_score_gemma":0.0003445688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006227595,"about_ca_topic_score_gemma":0.006641182,"domain_scores_codex":[0.9998583,0.00004083083,0.000009333377,0.00002161116,0.00004858956,0.00002137006],"domain_scores_gemma":[0.9996698,0.0001825582,0.00003275311,0.00001437843,0.00008911976,0.00001138304],"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":[0.001107491,0.0005458479,0.02093028,0.0001556484,0.00008118282,0.0001089284,0.00003819727,0.852457,0.04849812,0.0005257465,0.0002680297,0.07528345],"study_design_scores_gemma":[0.000006277383,0.0001499013,0.004871613,0.000002391491,0.00001353115,0.000009951581,0.0000139079,0.9732702,0.02139696,0.0001395077,0.0001189451,0.00000683537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926144,0.00008695716,0.006086925,0.00002700284,0.000008043729,0.00001724678,0.0001430093,0.00006011433,0.0009563714],"genre_scores_gemma":[0.9980285,0.00002992492,0.00141449,0.00000275218,9.97308e-7,0.000007401224,0.00007718919,0.000002743718,0.0004360593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006227595,"threshold_uncertainty_score":0.01238269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005999657697232807,"score_gpt":0.21018257329378,"score_spread":0.2041829155965472,"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."}}