{"id":"W2528518020","doi":"10.11159/ffhmt16.112","title":"Fuzzy Based Evaporator Model in Waste Heat Recovery System","year":2016,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Thermodynamic and Exergetic Analyses of Power and Cooling Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Evaporator; Waste heat; Waste heat recovery unit; Fuzzy logic; Waste management; Process engineering; Computer science; Environmental science; Engineering; Mechanical engineering; Heat exchanger; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001796739,0.000193821,0.0002543525,0.0001271803,0.00003233538,0.00004245582,0.0003358447,0.00009588608,0.00002046226],"category_scores_gemma":[0.000008461135,0.0001216804,0.0001125013,0.00008030031,0.00004949611,0.0001626397,0.00001580362,0.0001022562,0.000005196037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001063443,"about_ca_system_score_gemma":0.00003406729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001842018,"about_ca_topic_score_gemma":0.000005682735,"domain_scores_codex":[0.9989514,0.000005407058,0.0003359549,0.0002169993,0.000294583,0.0001956421],"domain_scores_gemma":[0.9996656,0.0000226391,0.00001076542,0.0000893441,0.0001485096,0.00006313985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000355201,0.00004306009,0.0006225827,0.000356294,0.0001232823,0.000001109467,0.0002613897,0.02121272,0.8983957,0.07699056,0.0003724924,0.001265643],"study_design_scores_gemma":[0.0008340225,0.00004538993,0.00004007665,0.001066613,0.00002842666,0.000002779916,0.0003528933,0.9649811,0.03068971,0.001711453,0.00003873797,0.0002088465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9282961,0.0001151749,0.02549678,0.000966856,0.0007647293,0.0002692493,0.0001133223,0.0001121779,0.04386555],"genre_scores_gemma":[0.999341,0.00009815129,0.000129686,0.00004659729,0.0000638546,0.00003123172,0.000002302993,0.00002273185,0.0002644152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9437683,"threshold_uncertainty_score":0.4961981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290027532315789,"score_gpt":0.204789871610679,"score_spread":0.1918895962875211,"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."}}