{"id":"W2182139230","doi":"","title":"ABSUM: a Knowledge-Based Abstractive Summarizer","year":2014,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Automatic summarization; Computer science; Natural language processing; Task (project management); Information retrieval; Knowledge base; Source text; Artificial intelligence; Representation (politics); Multi-document summarization; Scalability","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":[0.001102137,0.001118191,0.001001879,0.002547556,0.0005750541,0.001553872,0.001694134,0.0007836904,0.006110105],"category_scores_gemma":[0.003955911,0.000447579,0.0008145824,0.001377859,0.0003049196,0.001901371,0.001263046,0.001301453,0.004906965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005517417,"about_ca_system_score_gemma":0.0007241201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001660398,"about_ca_topic_score_gemma":0.003561935,"domain_scores_codex":[0.9991896,0.0001743031,0.0001002582,0.0001857168,0.0003012354,0.00004891023],"domain_scores_gemma":[0.9983196,0.0006194791,0.0002003231,0.000314892,0.0004692643,0.0000765484],"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":[0.0006199145,0.0001250544,0.0006602614,0.001008845,0.0001856299,0.0002268192,0.0004980225,0.01371058,0.04505648,0.006761785,0.03704207,0.8941046],"study_design_scores_gemma":[0.000388151,0.001089229,0.00449785,0.0002352555,0.0006216781,0.0007798774,0.0005723989,0.495695,0.1589835,0.03449282,0.3024212,0.0002232172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008571866,0.001301686,0.9514393,0.0003047812,0.0002310045,0.0002888446,0.00303723,0.03131003,0.003515313],"genre_scores_gemma":[0.113538,0.001001183,0.8585196,0.0003483499,0.0003799405,0.0006111178,0.0118422,0.001436402,0.01232322],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006110105,"threshold_uncertainty_score":0.02044034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02019895973292568,"score_gpt":0.2549944760805792,"score_spread":0.2347955163476536,"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."}}