{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002805552,0.00006713878,0.0001026158,0.0002387741,0.00007078474,0.0001257298,0.0002068369,0.0000373199,0.00001915815],"category_scores_gemma":[0.00005887852,0.00005728886,0.0000288448,0.001530585,0.000007312198,0.0004438691,0.00008341817,0.00005022494,0.00008787898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002649017,"about_ca_system_score_gemma":0.00004074367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005790278,"about_ca_topic_score_gemma":0.0004376443,"domain_scores_codex":[0.9991658,0.00005066947,0.0001889918,0.0002467644,0.0001889096,0.0001588489],"domain_scores_gemma":[0.9996502,0.00003302934,0.00004561937,0.0001788578,0.00006372872,0.00002850714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001139919,0.0002106928,0.2640324,0.00007939447,0.00008911317,0.00009697374,0.01031265,0.08308394,0.02360017,0.4629034,0.02285921,0.1327207],"study_design_scores_gemma":[0.0001193228,0.00001461526,0.04011456,0.00001132381,0.000002429161,4.964753e-7,0.00006730796,0.956563,0.001752345,0.000974427,0.0002962794,0.00008390237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1123418,0.00001488028,0.8831066,0.001506655,0.00009249096,0.0001327233,3.767618e-7,0.0002051607,0.002599249],"genre_scores_gemma":[0.9929091,0.00001497101,0.005636957,0.0003797924,0.00003613456,0.00001759361,0.00001375132,0.000004267967,0.00098745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8805673,"threshold_uncertainty_score":0.2336172,"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."}}