{"id":"W3153874716","doi":"10.48550/arxiv.2104.07058","title":"Predicting Discourse Trees from Transformer-based Neural Summarizers","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automatic summarization; Computer science; Transformer; Natural language processing; Artificial intelligence; Discourse analysis; Style (visual arts); Dependency (UML); Linguistics","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":[0.001066187,0.0007314065,0.00043504,0.001461178,0.0002262619,0.0007021845,0.0006147303,0.000584838,0.001322544],"category_scores_gemma":[0.006898165,0.0002274533,0.0004926959,0.000844115,0.0001720589,0.001436475,0.000417663,0.000915667,0.0009227717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006810273,"about_ca_system_score_gemma":0.0004643717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002242893,"about_ca_topic_score_gemma":0.007118904,"domain_scores_codex":[0.9995492,0.0001833486,0.0000275535,0.000142885,0.00005557824,0.00004153933],"domain_scores_gemma":[0.9965863,0.002455404,0.0002210587,0.0001679941,0.000494762,0.00007434404],"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":[0.0009014232,0.0002443525,0.01444494,0.0007918341,0.0002609296,0.0002427866,0.001012034,0.277762,0.02873409,0.009395488,0.01508232,0.6511278],"study_design_scores_gemma":[0.00002626513,0.0001118323,0.002504626,0.00003380125,0.00006342916,0.00004084202,0.0001082109,0.9784589,0.009237289,0.007495892,0.001906092,0.00001279916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4717903,0.002963005,0.5094274,0.0007700186,0.0001697903,0.0001790956,0.005594944,0.005052013,0.00405342],"genre_scores_gemma":[0.9045696,0.0005406025,0.08342214,0.00005893099,0.00008528592,0.00008641584,0.008663302,0.0001250936,0.002448709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002242893,"threshold_uncertainty_score":0.005638659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06890917542870136,"score_gpt":0.1956830011154065,"score_spread":0.1267738256867052,"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."}}