{"id":"W1999236506","doi":"10.1115/msec2011-50178","title":"A Quantitative Study of Illumination Techniques for Machine Vision Based Inspection","year":2011,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Backlight; Computer science; Computer vision; Task (project management); Machine vision; Sample (material); Artificial intelligence; Set (abstract data type); Field (mathematics); Engineering; Mathematics; Liquid-crystal display","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":[],"consensus_categories":[],"category_scores_codex":[0.0002720002,0.0000764813,0.0001281241,0.0002049344,0.00004401316,0.000006408733,0.00003332318,0.00006856665,0.00002669563],"category_scores_gemma":[0.00003356973,0.00006461326,0.00003965987,0.0001858864,0.000008216983,0.0001108429,0.000004563315,0.00004932912,0.000002645922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000353481,"about_ca_system_score_gemma":0.000004233542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003651637,"about_ca_topic_score_gemma":0.000154228,"domain_scores_codex":[0.9994738,0.00002881056,0.000237098,0.00009621185,0.00009818821,0.00006588715],"domain_scores_gemma":[0.9996759,0.00004237041,0.00005149136,0.0001001572,0.0001136749,0.00001644645],"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":[0.004251164,0.005629272,0.006246443,0.001011634,0.0005268265,0.000007630028,0.02860264,0.004687962,0.5564262,0.01321751,0.00662082,0.3727719],"study_design_scores_gemma":[0.002040939,0.01031729,0.005232627,0.00007227172,0.00004291043,0.000001762399,0.004189024,0.3250569,0.6517881,0.0001985736,0.0007799783,0.0002796762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5916513,0.00001075323,0.4003766,0.000001846501,0.0002983275,0.001058124,0.000005456468,0.0005665823,0.006031116],"genre_scores_gemma":[0.9953936,7.276429e-7,0.004441803,0.000002532629,0.00002531468,0.00009063457,0.000002925491,0.00001544738,0.00002705938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4037423,"threshold_uncertainty_score":0.2634852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05175895301781711,"score_gpt":0.2935615058805196,"score_spread":0.2418025528627025,"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."}}