{"id":"W2153404309","doi":"10.1109/iecon.1990.149245","title":"An experimental vision system for SMD component placement inspection","year":2002,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Centroid; Component (thermodynamics); Artificial intelligence; Orientation (vector space); Computer vision; Surface-mount technology; Computer science; Printed circuit board; Displacement (psychology); Segmentation; Soldering; Mathematics; Materials science; Geometry; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009527785,0.0005236416,0.000586341,0.001024846,0.0005161847,0.0006558133,0.001271449,0.001065727,0.0148102],"category_scores_gemma":[0.001692142,0.0003257388,0.000232901,0.0006856759,0.0003253356,0.0006678352,0.0006233764,0.0006976916,0.003848619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006633439,"about_ca_system_score_gemma":0.0008670597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001669749,"about_ca_topic_score_gemma":0.001582712,"domain_scores_codex":[0.9988735,0.0001288818,0.00006303252,0.0002984708,0.0005512036,0.00008489512],"domain_scores_gemma":[0.9988111,0.0001587594,0.00006447473,0.0003125787,0.0005344522,0.0001185902],"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":[0.0009667412,0.0008130225,0.001732005,0.0006013565,0.00005076862,0.0002080533,0.0001600739,0.006522162,0.7279466,0.002716359,0.00977168,0.2485113],"study_design_scores_gemma":[0.0007297558,0.006656645,0.01569447,0.0000896935,0.0001071841,0.001570807,0.0001139646,0.1840291,0.7262605,0.001302574,0.0632879,0.0001573417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1720174,0.0004068964,0.785102,0.0002327484,0.0004865354,0.00225224,0.002535228,0.02477367,0.01219337],"genre_scores_gemma":[0.3899768,0.0002319919,0.5905038,0.0003179911,0.00006337052,0.002490424,0.003301995,0.0006367436,0.01247698],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0148102,"threshold_uncertainty_score":0.04954505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0282102653395263,"score_gpt":0.257533119255743,"score_spread":0.2293228539162167,"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."}}