{"id":"W3042721654","doi":"10.1109/icpr48806.2021.9413149","title":"Relatable Clothing: Detecting Visual Relationships between People and Clothing","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Clothing; Biometrics; Computer science; Artificial intelligence; Visibility; Segmentation; Field (mathematics); Computer vision; Pattern recognition (psychology); Geography; Mathematics","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001488777,0.0003501671,0.0005257583,0.0001534551,0.000752759,0.001586836,0.0006342782,0.0004277462,0.00002852045],"category_scores_gemma":[0.0006722342,0.000350728,0.000140671,0.0003796481,0.00003763442,0.0009263344,0.003266623,0.001597962,0.00001194359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008509935,"about_ca_system_score_gemma":0.000184544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006971723,"about_ca_topic_score_gemma":0.0003023617,"domain_scores_codex":[0.9970782,0.000566282,0.0005092691,0.001089161,0.0003361095,0.0004209992],"domain_scores_gemma":[0.9977041,0.0009352738,0.0002759178,0.0007311748,0.0001681291,0.0001854398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002229735,0.0002515719,0.4971175,0.0009587108,0.001599903,0.0001613109,0.05863205,0.1407047,0.003609856,0.02170431,0.002182454,0.2730553],"study_design_scores_gemma":[0.0003887357,0.0000634747,0.05441634,0.0004453697,0.0001497045,0.00003324759,0.001303888,0.9304893,0.004101087,0.006185817,0.001092376,0.00133069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08230455,0.0007915251,0.9126875,0.0006848865,0.0006992303,0.0002221813,0.000002169543,0.0002715327,0.002336417],"genre_scores_gemma":[0.7658778,0.00006001175,0.2331646,0.00006668046,0.0003967052,0.00001421373,0.00001392361,0.00002485806,0.0003812016],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7897846,"threshold_uncertainty_score":0.9998945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03989076297895446,"score_gpt":0.2646250684358539,"score_spread":0.2247343054568994,"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."}}