{"id":"W4237006680","doi":"10.1109/cccrv.2004.1301409","title":"Proceedings 1st Canadian Conference on Computer and Robot Vision 2004","year":2004,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Robot; Computer vision; Computer graphics (images); Human–computer interaction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001616684,0.001531061,0.001877457,0.002211277,0.00191899,0.004828484,0.002699001,0.001766761,0.1602843],"category_scores_gemma":[0.002604616,0.0008567545,0.0009999484,0.002138297,0.001699565,0.002757756,0.00181207,0.00191666,0.06914699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003675386,"about_ca_system_score_gemma":0.01093652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2389335,"about_ca_topic_score_gemma":0.3254006,"domain_scores_codex":[0.9989261,0.0001035865,0.00004225679,0.0001865698,0.0005883453,0.0001530385],"domain_scores_gemma":[0.9965143,0.0002277933,0.00003669139,0.0003685374,0.002543094,0.0003096322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002197954,0.0001409625,0.0008009551,0.0003144939,0.00005404816,0.0001103469,0.0000916697,0.001077126,0.00448195,0.007147705,0.4990664,0.4864945],"study_design_scores_gemma":[0.00003702868,0.00006497608,0.00263834,0.0001590991,0.000119436,0.0003299031,0.0002785371,0.01341442,0.005664705,0.008279948,0.9689483,0.00006540518],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.02012932,0.06579127,0.4074796,0.02128085,0.04109112,0.0007438751,0.006398655,0.02638355,0.4107018],"genre_scores_gemma":[0.04368038,0.03127712,0.08389855,0.001088952,0.001500473,0.0001674479,0.007722557,0.001533218,0.8291313],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2389335,"threshold_uncertainty_score":0.5362046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159722184038017,"score_gpt":0.210024956016633,"score_spread":0.1940527376128313,"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."}}