{"id":"W2151552691","doi":"10.1162/089120102762671963","title":"Generating Indicative-Informative Summaries with SumUM","year":2002,"lang":"en","type":"article","venue":"Computational Linguistics","topic":"Topic Modeling","field":"Computer Science","cited_by":140,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Université de Montréal; McGill University","keywords":"Automatic summarization; Computer science; Identification (biology); Information retrieval; Natural language processing; Process (computing); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0032882,0.001026326,0.0008721785,0.001726694,0.0006755776,0.002016862,0.001017503,0.0007514986,0.003921166],"category_scores_gemma":[0.01550213,0.000294746,0.000505013,0.001574542,0.000339388,0.002873464,0.001483337,0.0006341445,0.002071163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003729771,"about_ca_system_score_gemma":0.0005408053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005752751,"about_ca_topic_score_gemma":0.0009960994,"domain_scores_codex":[0.9977459,0.001182842,0.0002247231,0.0003146676,0.000468852,0.0000629391],"domain_scores_gemma":[0.9915404,0.005170198,0.0007743528,0.0008941223,0.001432848,0.0001881823],"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":[0.001014773,0.0002865345,0.002052643,0.00186472,0.0001974389,0.0004094316,0.002920011,0.0216078,0.04772545,0.009200629,0.01726666,0.8954539],"study_design_scores_gemma":[0.000514128,0.001936246,0.005025861,0.0002635838,0.0006082543,0.0008584086,0.00228446,0.6160976,0.2331996,0.02120404,0.1177602,0.0002476877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09463151,0.00179078,0.8724024,0.0005623887,0.000254802,0.0005361673,0.001425215,0.02375864,0.004638192],"genre_scores_gemma":[0.2527396,0.0006821218,0.735935,0.0001666541,0.0001914647,0.0004197634,0.004523207,0.0009616152,0.004380449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003921166,"threshold_uncertainty_score":0.01738983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02829016747849478,"score_gpt":0.2487386652571547,"score_spread":0.2204484977786599,"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."}}