{"id":"W4404791709","doi":"10.18653/v1/2022.aacl-demo.1","title":"VScript: Controllable Script Generation with Visual Presentation","year":2022,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Presentation (obstetrics); Computer graphics (images); Artificial intelligence; Programming language","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":[0.001274299,0.001938533,0.0007408166,0.0009221319,0.0004947108,0.001876514,0.003452926,0.001215401,0.07602561],"category_scores_gemma":[0.004449858,0.0009707749,0.001200218,0.0005764779,0.0006483257,0.002156532,0.002982701,0.00139525,0.02561808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004200801,"about_ca_system_score_gemma":0.0006122671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00088383,"about_ca_topic_score_gemma":0.0009373517,"domain_scores_codex":[0.9992022,0.0001631114,0.00006885836,0.000167926,0.000306626,0.00009131843],"domain_scores_gemma":[0.998494,0.0005980711,0.00006300798,0.0004211497,0.0002978659,0.000126011],"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":[0.001760033,0.0004044468,0.001053986,0.00109649,0.0001425679,0.00113649,0.0007018125,0.01469959,0.0777136,0.04422262,0.3922046,0.4648636],"study_design_scores_gemma":[0.000850082,0.0004110517,0.0007799899,0.000247515,0.0001160765,0.0008963645,0.0002238293,0.3545735,0.1895762,0.05649819,0.395594,0.0002332436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004182086,0.0001755468,0.7245986,0.0001811215,0.0005498866,0.0002786123,0.003179975,0.2545291,0.01232521],"genre_scores_gemma":[0.1836756,0.0005723828,0.6548564,0.000579848,0.0002390508,0.001762057,0.02076519,0.08645977,0.05108972],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07602561,"threshold_uncertainty_score":0.254331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368084723915391,"score_gpt":0.2683348793399821,"score_spread":0.2546540321008282,"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."}}