{"id":"W2809668489","doi":"","title":"Modélisation électro-magnéto-thermique et optimisation des paramètres de chauffe d'un nouveau système de traitement thermique par induction robotisé","year":2018,"lang":"fr","type":"article","venue":"Espace École de technologie supérieure (École de technologie supérieure)","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.003388542,0.001738356,0.001426723,0.001278673,0.001029721,0.0005452098,0.002124246,0.005104054,0.0004949565],"category_scores_gemma":[0.002871664,0.001931083,0.0005012008,0.002258359,0.001963761,0.001361312,0.0006769597,0.00314385,0.000206214],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00418602,"about_ca_system_score_gemma":0.001178283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656907,"about_ca_topic_score_gemma":0.002632002,"domain_scores_codex":[0.991679,0.0007009653,0.001488053,0.001701751,0.000657181,0.003773041],"domain_scores_gemma":[0.9957503,0.0003783376,0.0007321204,0.002171638,0.0004741761,0.0004934267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004363186,0.000753464,0.00484996,0.001122017,0.0006889224,0.0004686617,0.005207274,0.5187642,0.3870554,0.03239306,0.001871578,0.04638916],"study_design_scores_gemma":[0.001997973,0.00202356,0.008999011,0.001132548,0.0005348007,0.001205133,0.006342703,0.2206839,0.6871575,0.05806567,0.009281831,0.00257539],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5876808,0.00240276,0.3928405,0.006237918,0.0009676288,0.001953841,0.00009146717,0.007130024,0.0006951294],"genre_scores_gemma":[0.9147843,0.002808579,0.07808715,0.0005695066,0.0005955218,0.001472307,0.0001127073,0.0004145295,0.001155453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3271035,"threshold_uncertainty_score":0.9996367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946562458179332,"score_gpt":0.2580509882123265,"score_spread":0.2385853636305332,"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."}}