{"id":"W2805310589","doi":"10.11159/ffhmt18.189","title":"Optimal Control of a Stirling Engine","year":2018,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer","topic":"Advanced Thermodynamic Systems and Engines","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stirling engine; Stirling cycle; Computer science; Control (management); Environmental science; Engineering; Mechanical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00102714,0.001417373,0.001168263,0.0006256522,0.0008427154,0.002446098,0.0009462347,0.001308345,0.003646311],"category_scores_gemma":[0.001439887,0.0006243152,0.0005593775,0.0003064034,0.001472486,0.0007071411,0.001213406,0.001078931,0.0005583258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001407419,"about_ca_system_score_gemma":0.001594478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306578,"about_ca_topic_score_gemma":0.006467459,"domain_scores_codex":[0.9995064,0.0001192893,0.00001952404,0.0001159186,0.0001282307,0.0001106948],"domain_scores_gemma":[0.9995055,0.0001802488,0.00008091925,0.00001775832,0.0001624827,0.00005302181],"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":[0.0003073283,0.00009571265,0.0002898221,0.0001600919,0.00003859356,0.0001096621,0.00007934714,0.9601392,0.009066518,0.01602748,0.001116212,0.01257009],"study_design_scores_gemma":[0.00004139617,0.0001057794,0.0001173684,0.000008119593,0.000009956497,0.000006079317,0.00001093282,0.9966935,0.0006734314,0.001725386,0.0005965979,0.00001151976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1326039,0.001906587,0.7865961,0.001227807,0.0006392653,0.0002514453,0.0001909707,0.0006460179,0.07593799],"genre_scores_gemma":[0.9843808,0.0003070605,0.008436915,0.00007747639,0.000058356,0.0000789318,0.00004408519,0.00002273039,0.006593591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01306578,"threshold_uncertainty_score":0.02597946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118105429279319,"score_gpt":0.2120573671576285,"score_spread":0.2008763128648354,"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."}}