{"id":"W4401698507","doi":"10.3390/s24165355","title":"Eddy Current Sensor Probe Design for Subsurface Defect Detection in Additive Manufacturing","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Eddy current; Surface roughness; Surface finish; Composite material; RADIUS; Fusion; Engineering; Computer science; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001895538,0.0002369809,0.000198699,0.000154062,0.00005567979,0.0001064802,0.00006554913,0.00007989423,0.00006740059],"category_scores_gemma":[0.00004349637,0.0002219619,0.00008888746,0.0001007656,0.00002154167,0.0001223944,0.00001445714,0.0001796146,0.00007971637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157012,"about_ca_system_score_gemma":0.00001498474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001010814,"about_ca_topic_score_gemma":0.0000234713,"domain_scores_codex":[0.9990003,0.00004651792,0.0002111509,0.0002956687,0.00010115,0.0003452575],"domain_scores_gemma":[0.9994847,0.0003192697,0.00002013678,0.0001031901,0.00002233472,0.00005038315],"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":[0.0002195846,0.00005408594,0.00001082876,0.004845453,0.0002336566,0.00009595493,0.002128497,0.621101,0.06212499,0.0001097887,0.001362497,0.3077137],"study_design_scores_gemma":[0.000166907,0.00004907651,0.0003017106,0.0002298313,0.00002558808,0.00001080186,0.00006574889,0.02481768,0.9507551,0.0007558148,0.02252953,0.0002921913],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8706406,0.001068462,0.1245971,0.0000164994,0.001728719,0.0007938484,0.0001772048,0.0008033679,0.0001742732],"genre_scores_gemma":[0.9975759,0.0002051373,0.001620723,0.000004205055,0.0002799369,0.0001360326,0.00002373988,0.00007644667,0.0000778441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8886302,"threshold_uncertainty_score":0.9051344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01963645425290475,"score_gpt":0.244561266304982,"score_spread":0.2249248120520772,"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."}}