{"id":"W4416367682","doi":"10.1109/iscit67082.2025.11231578","title":"Deep Learning-Enhanced Push-Broom Hyperspectral Imaging System for Non-Destructive Subsurface Defect Detection","year":2025,"lang":"","type":"article","venue":"","topic":"Surface Roughness and Optical Measurements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperspectral imaging; Image resolution; Pattern recognition (psychology); Feature extraction; Resolution (logic); Translation (biology); Feature (linguistics); Spectral analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006272961,0.0007656935,0.000857853,0.000277377,0.0006724457,0.0003512607,0.0003369809,0.0003269431,0.00006454286],"category_scores_gemma":[0.0003425131,0.0008208613,0.0006117808,0.0009424873,0.00009122051,0.0004828216,0.00008676363,0.0007543044,0.00009524288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001713031,"about_ca_system_score_gemma":0.00009073005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001476932,"about_ca_topic_score_gemma":0.0001141289,"domain_scores_codex":[0.996277,0.0001364169,0.0008209758,0.001014069,0.0004409288,0.001310611],"domain_scores_gemma":[0.9982274,0.0004253323,0.0001465413,0.0004704162,0.0004886849,0.0002416284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007505411,0.0001550201,0.004422,0.003852674,0.001681636,0.0000124915,0.001200313,0.3856205,0.5062065,0.003467245,0.00001908718,0.09261204],"study_design_scores_gemma":[0.002429828,0.000163092,0.003334407,0.0006936818,0.0005232936,0.000007388319,0.006222758,0.57921,0.4062302,0.000251034,0.0001456247,0.0007887026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.35982,0.001730674,0.6169837,0.00003833927,0.003601026,0.001273409,0.000004237651,0.0005427127,0.01600594],"genre_scores_gemma":[0.9904928,0.00007974279,0.0082831,0.0000157163,0.00017525,0.0002305785,0.000004970139,0.0001326633,0.0005851655],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6306728,"threshold_uncertainty_score":0.9994242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006826781996708772,"score_gpt":0.2242746101829265,"score_spread":0.2174478281862177,"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."}}