{"id":"W2180876289","doi":"10.1007/978-1-4471-6741-9_1","title":"Industrial Inspection with Open Eyes: Advance with Machine Vision Technology","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Machine vision; Computer vision; Artificial intelligence; Computer science; Manufacturing engineering; Engineering; Engineering drawing","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":[0.0002742345,0.0005352702,0.0006697939,0.0006734715,0.0001223896,0.0001873901,0.0002187047,0.0006846936,0.00006673631],"category_scores_gemma":[0.000005535661,0.0004168602,0.00004028718,0.000219763,0.00009735978,0.0009758958,0.0001483709,0.0009475506,0.00005754912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001828103,"about_ca_system_score_gemma":0.00003130797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003200275,"about_ca_topic_score_gemma":0.0004978498,"domain_scores_codex":[0.9981256,0.00004287955,0.0005465043,0.0006640134,0.0003574778,0.0002635536],"domain_scores_gemma":[0.9990597,0.00006526449,0.0002672129,0.0003211833,0.0001739261,0.0001126832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003690015,0.00002423532,0.0001103064,0.00008276463,0.00003091124,0.0000633503,0.00003890414,0.001455026,0.000009040222,0.00005557797,0.0004480862,0.9973128],"study_design_scores_gemma":[0.01556583,0.01234264,0.0001028222,0.01671624,0.0001525573,0.001247283,0.00009468604,0.04669281,0.0002406756,0.01002152,0.8938326,0.002990339],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03365751,0.01989645,0.6760656,0.0004361851,0.01296236,0.0112406,0.0007594033,0.004389395,0.2405925],"genre_scores_gemma":[0.9595841,0.01279931,0.01375155,0.000438968,0.004720752,0.0003803073,0.001585236,0.000980837,0.005758935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9943225,"threshold_uncertainty_score":0.9998283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0327627359289742,"score_gpt":0.2727255303335905,"score_spread":0.2399627944046163,"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."}}