{"id":"W3204365976","doi":"10.1002/adem.202100877","title":"Material Selection Methodology for an Induction Welding Magnetic Susceptor Based on Hysteresis Losses","year":2021,"lang":"en","type":"article","venue":"Advanced Engineering Materials","topic":"Advanced Welding Techniques Analysis","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; École de Technologie Supérieure","funders":"Science and Engineering Research Council","keywords":"Susceptor; Materials science; Induction heating; Hysteresis; Electromagnetic induction; Magnetic field; Welding; Electromagnetic coil; Magnetic hysteresis; Composite material; Induction coil; Ferrimagnetism; Magnetization; Condensed matter physics; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003028074,0.0003456973,0.0004935777,0.0002555753,0.00008191522,0.00009868893,0.0001473942,0.0001973217,0.0002677192],"category_scores_gemma":[0.0002482698,0.0004030338,0.00008967555,0.0003134308,0.00001522438,0.0003261518,0.000023097,0.0001066836,0.0000064716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001964326,"about_ca_system_score_gemma":0.00001704015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007565725,"about_ca_topic_score_gemma":0.000005620204,"domain_scores_codex":[0.9984405,0.00008481538,0.0004382863,0.0004416227,0.0001388834,0.0004558787],"domain_scores_gemma":[0.9991695,0.0001905029,0.00006778129,0.0003713562,0.0001107381,0.00009007342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004017056,0.00001176541,0.000002488106,0.0001482379,0.00001665828,0.000001916177,0.000009984567,0.4241776,0.5734633,0.0001378788,0.00002837744,0.00196158],"study_design_scores_gemma":[0.0003448414,0.0002446263,0.000104333,0.00008736421,0.00005936532,0.00001199935,0.00001784903,0.03910429,0.9579973,0.0003754744,0.001247168,0.0004054422],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5289731,0.00003259704,0.4678434,0.00001860677,0.001495137,0.0002529443,0.00006904817,0.001291058,0.00002410438],"genre_scores_gemma":[0.644401,0.00002747553,0.3546988,0.00002441001,0.000323246,0.0002389141,0.0001425273,0.0001192151,0.00002446027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3850733,"threshold_uncertainty_score":0.9998422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028361182911421,"score_gpt":0.2808855308613614,"score_spread":0.2525243479499404,"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."}}