{"id":"W4390873040","doi":"10.1109/iccv51070.2023.00279","title":"GePSAn: Generative Procedure Step Anticipation in Cooking Videos","year":2023,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Anticipation (artificial intelligence); Generative grammar; Artificial intelligence; Domain (mathematical analysis); Generative model; Machine learning; Natural language processing","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":[0.0009468009,0.0009430166,0.0005832938,0.0007901035,0.0004214604,0.0007728168,0.001613654,0.001151044,0.005855637],"category_scores_gemma":[0.004594156,0.0006035247,0.001133636,0.000578267,0.0006433608,0.001454588,0.0009330698,0.001876078,0.001476673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051049,"about_ca_system_score_gemma":0.0008153986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01353663,"about_ca_topic_score_gemma":0.02746245,"domain_scores_codex":[0.9995832,0.0001325331,0.00001268302,0.0001754554,0.00004937538,0.00004686573],"domain_scores_gemma":[0.9984744,0.001193729,0.00006773994,0.0001201269,0.00008278826,0.00006117787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005995891,0.0002109782,0.008101312,0.0003686378,0.0001770284,0.0007136647,0.0006293079,0.7267624,0.008559518,0.02924386,0.01458536,0.2100484],"study_design_scores_gemma":[0.00001635761,0.00003319293,0.0006703149,0.0000191484,0.00001337478,0.00006526554,0.00003506792,0.9851461,0.001326663,0.01048867,0.00217318,0.00001268801],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1043579,0.001578517,0.8728009,0.001129005,0.0001827118,0.0002264434,0.00364853,0.007553786,0.008522092],"genre_scores_gemma":[0.7844929,0.0007797203,0.1905826,0.0005633782,0.0001183303,0.0004284973,0.00902612,0.0007974491,0.01321105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01353663,"threshold_uncertainty_score":0.02691567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02301005274985482,"score_gpt":0.2740819549110001,"score_spread":0.2510719021611453,"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."}}