{"id":"W4225162688","doi":"10.3390/en15093249","title":"Advances in Thermal Management Technologies of Electrical Machines","year":2022,"lang":"en","type":"article","venue":"Energies","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Thermal management of electronic devices and systems; Water cooling; Armature (electrical engineering); Mechanical engineering; Thermal; Torque; Automotive engineering; Computer science; Electrical engineering; Engineering; Electromagnetic coil; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0009918181,0.0006637574,0.0007323184,0.001654384,0.0002327667,0.001184255,0.000750682,0.0006204596,0.001971717],"category_scores_gemma":[0.001679598,0.0004277823,0.0007287945,0.001789503,0.000460961,0.002276539,0.000444342,0.0007263003,0.0005367228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006127449,"about_ca_system_score_gemma":0.0009121799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005014841,"about_ca_topic_score_gemma":0.0006836955,"domain_scores_codex":[0.9991986,0.0001796318,0.00009858373,0.0001685462,0.000311463,0.00004305831],"domain_scores_gemma":[0.9990857,0.0005250315,0.0001319002,0.0000469291,0.0001982777,0.00001220784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009034106,0.00008986964,0.0009775547,0.03129616,0.0001480292,0.0001602421,0.0002862932,0.01136627,0.02571453,0.03530873,0.004588775,0.8899732],"study_design_scores_gemma":[0.00002833834,0.0005649449,0.00444612,0.009117706,0.0004711341,0.001303145,0.0003720332,0.01748616,0.04827127,0.02931573,0.888504,0.0001194214],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.009516845,0.9204541,0.05277223,0.0006244518,0.000390462,0.00006704349,0.0001043341,0.0001135967,0.01595704],"genre_scores_gemma":[0.0995957,0.857864,0.03597756,0.0003103011,0.0006475777,0.0001378241,0.0001885031,0.00007494704,0.005203604],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001971717,"threshold_uncertainty_score":0.006596088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003073318299142079,"score_gpt":0.188100942566737,"score_spread":0.1850276242675949,"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."}}