{"id":"W4318211862","doi":"10.1109/tip.2022.3232009","title":"IEEE Transactions on Image Processing publication information","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"College of Engineering, Michigan State University; Centre National de la Recherche Scientifique; Chinese Academy of Sciences; Academia Sinica; École Polytechnique Fédérale de Lausanne; Politecnico di Torino; Institut national de recherche en informatique et en automatique (INRIA); Universidad Nacional de Colombia; Université Catholique de Louvain; Google; Arizona State University; McMaster University; Johns Hopkins University","keywords":"Computer science; Image processing; Document image processing; Transaction processing; Computer vision; Information retrieval; Information processing; Image (mathematics); Computer graphics (images); Artificial intelligence; Image segmentation; Database; Database transaction","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0005023436,0.0003719025,0.0003000312,0.0009008481,0.001864366,0.000712404,0.0002301997,0.0001746621,0.0004276241],"category_scores_gemma":[0.000008592433,0.0004108905,0.0001869826,0.001454941,0.00005696544,0.003316736,7.941512e-7,0.001165187,0.0002214055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005975126,"about_ca_system_score_gemma":0.0001567605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003713405,"about_ca_topic_score_gemma":0.000006910504,"domain_scores_codex":[0.997578,0.0001047751,0.0007625317,0.0003581978,0.0007278884,0.0004686356],"domain_scores_gemma":[0.9989462,0.00005418896,0.0002094194,0.000328183,0.0003152667,0.0001467809],"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":[0.0001322572,0.0001708595,2.930341e-7,0.0002811236,0.00003321175,0.00000336434,0.001497188,0.1804111,0.02460917,0.000002103026,0.0008078237,0.7920516],"study_design_scores_gemma":[0.002178373,0.0004527215,0.00001569003,0.0002692239,0.0001436833,0.000136485,0.002513852,0.6064163,0.3672938,0.0000565348,0.01940153,0.001121785],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006229141,0.00006181811,0.9860978,0.0001763471,0.001669353,0.0006161029,0.0001129483,0.001294374,0.003742192],"genre_scores_gemma":[0.9967356,0.00001621983,0.001758751,0.0001986714,0.0001241095,0.0006502111,0.00001859145,0.00008783126,0.0004100664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9905064,"threshold_uncertainty_score":0.9998343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01560890400085701,"score_gpt":0.2406192100408223,"score_spread":0.2250103060399653,"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."}}