{"id":"W2789321111","doi":"10.1002/cjce.23150","title":"An automatic refrigerant circuit generation method for finned‐tube heat exchangers","year":2018,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Heat Transfer and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Refrigerant; Heat exchanger; Electronic circuit; Computer science; Tube (container); Electromagnetic coil; Micro heat exchanger; Mechanical engineering; Simulation; Engineering; Plate heat exchanger; Electrical engineering","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":[0.0003733252,0.0001181385,0.0001631176,0.0001226625,0.00007306806,0.00006377894,0.000179952,0.00008564722,0.00005112174],"category_scores_gemma":[0.00005376512,0.00009809583,0.0000672928,0.0001404849,0.00002223794,0.0001522847,0.000001316298,0.0001605865,0.000001946235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002104968,"about_ca_system_score_gemma":0.0001174311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000164233,"about_ca_topic_score_gemma":0.0002781641,"domain_scores_codex":[0.9992781,0.00001351881,0.0002689839,0.00006996697,0.0001000041,0.0002693939],"domain_scores_gemma":[0.9993724,0.00005028439,0.00001134106,0.0001311753,0.0001111524,0.000323693],"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":[0.000002927294,0.000003282173,0.000003347379,0.00006459466,0.00005436807,0.000004511722,0.001349861,0.4391772,0.5524569,0.0002849851,0.0006926567,0.005905453],"study_design_scores_gemma":[0.0001772012,0.00004263455,0.000008001356,0.00003251054,0.00002739193,0.00004616578,0.000005632243,0.8031736,0.1956746,0.00005697575,0.0006521287,0.0001032253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1800765,0.0002010844,0.8185697,0.0002446079,0.0006062629,0.0001402407,0.0000115813,0.00005623373,0.00009385154],"genre_scores_gemma":[0.9792674,0.000002896504,0.0195848,0.00008593906,0.001000099,0.000007772515,0.00000830403,0.00003965485,0.000003144939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7991909,"threshold_uncertainty_score":0.4000232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02017348216278169,"score_gpt":0.2313201240843845,"score_spread":0.2111466419216028,"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."}}