{"id":"W4311719620","doi":"10.32985/ijeces.13.9.9","title":"ResViT","year":2022,"lang":"en","type":"article","venue":"International journal of electrical and computer engineering systems","topic":"Generative Adversarial Networks and Image Synthesis","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Extractor; Artificial intelligence; Feature extraction; Pattern recognition (psychology); Feature (linguistics); Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005833438,0.001426339,0.0005523968,0.0008241177,0.0004635642,0.001206963,0.001829565,0.001248652,0.02087733],"category_scores_gemma":[0.002087013,0.0003774563,0.0007777791,0.0004649289,0.0003833949,0.002185907,0.001572123,0.001431136,0.01194744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009939764,"about_ca_system_score_gemma":0.0008957185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006025463,"about_ca_topic_score_gemma":0.01006593,"domain_scores_codex":[0.999527,0.00005056609,0.00002074338,0.0001596871,0.0001556062,0.00008648715],"domain_scores_gemma":[0.9995932,0.00005990307,0.00002560851,0.0001808098,0.0001120411,0.00002844187],"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":[0.000768546,0.0003813988,0.003934621,0.0005674295,0.00017043,0.0003288095,0.00009786922,0.06005045,0.02497423,0.01910206,0.2511074,0.6385167],"study_design_scores_gemma":[0.0001439294,0.0004505198,0.003221864,0.0001136624,0.00006061363,0.0008189938,0.00008745444,0.7356921,0.05346251,0.02227806,0.1835851,0.00008521862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1259157,0.005128456,0.5441816,0.002493497,0.002245306,0.001218235,0.02883223,0.1434207,0.1465643],"genre_scores_gemma":[0.5642525,0.00145671,0.2449998,0.002634272,0.000259568,0.0008368316,0.07841789,0.003415645,0.1037268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02087733,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005166113242905878,"score_gpt":0.1874651390925524,"score_spread":0.1822990258496465,"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."}}