{"id":"W4256292777","doi":"10.1109/tcsvt.2019.2940862","title":"IEEE Transactions on Circuits and Systems for Video Technology publication information","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems for Video Technology","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Electronic circuit; Multimedia; Engineering; Electrical engineering","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":[0.0006014105,0.0004878911,0.0008067459,0.002443294,0.0005430807,0.0002884631,0.0002375247,0.001213934,0.0000112164],"category_scores_gemma":[0.00003539216,0.0004882062,0.0001767807,0.001078837,0.0001063438,0.0007686005,0.000001088168,0.0006406836,0.00008106973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002959078,"about_ca_system_score_gemma":0.00005714316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009811998,"about_ca_topic_score_gemma":0.00002765931,"domain_scores_codex":[0.9972728,0.00005746144,0.001126905,0.0006032223,0.0003011191,0.0006384592],"domain_scores_gemma":[0.9980868,0.0003197428,0.0003050865,0.0006691985,0.0004729772,0.0001462349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003080527,0.0004077613,0.0001073221,0.006262392,0.001425752,0.000005262434,0.0009948597,0.1691,0.07308687,0.01536421,0.004497158,0.7284404],"study_design_scores_gemma":[0.01449696,0.006482499,0.00004973236,0.002226376,0.0006557428,0.001640336,0.006639794,0.5005566,0.1236161,0.001034313,0.339368,0.003233468],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08397668,0.0006846691,0.9011177,0.0002345705,0.006481295,0.005073372,0.0004921649,0.001609934,0.0003296202],"genre_scores_gemma":[0.996108,0.0001621246,0.0000274109,0.00005179451,0.0001103077,0.003050315,0.0000139274,0.00008829628,0.0003878121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9121313,"threshold_uncertainty_score":0.9997569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951575535576111,"score_gpt":0.2310904835398625,"score_spread":0.2115747281841014,"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."}}