{"id":"W2096537984","doi":"","title":"Using coreference links and sentence compression in graph-based summarization","year":2008,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automatic summarization; Coreference; Computer science; Sentence; Natural language processing; Graph; Artificial intelligence; Multi-document summarization; Information retrieval; Theoretical computer science; Resolution (logic)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002909478,0.0009304636,0.0007920102,0.002590011,0.0006853081,0.001195164,0.0009442451,0.0009743617,0.002340786],"category_scores_gemma":[0.01557652,0.0003695303,0.0006544739,0.002487184,0.0003415835,0.003270633,0.0008813958,0.0009940052,0.001218724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003901203,"about_ca_system_score_gemma":0.0005166299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002110298,"about_ca_topic_score_gemma":0.00334897,"domain_scores_codex":[0.9975496,0.00138296,0.0002080601,0.0003915495,0.0003836249,0.00008413757],"domain_scores_gemma":[0.9876146,0.008677876,0.0008123108,0.001090477,0.001673518,0.0001311422],"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":[0.0008705679,0.0001837873,0.002407124,0.0009026861,0.0002761141,0.0002565447,0.001511948,0.03653732,0.1001298,0.004938636,0.01299284,0.8389927],"study_design_scores_gemma":[0.0002271151,0.001015066,0.004821131,0.0001263167,0.0005859151,0.0004988844,0.0007827423,0.7467353,0.181737,0.03081429,0.03245518,0.0002010979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09566187,0.001200208,0.8844607,0.0007201838,0.0001527232,0.0003780899,0.001237089,0.01356531,0.002623809],"genre_scores_gemma":[0.3339185,0.0007140012,0.6567363,0.0003139445,0.0002095306,0.000258704,0.004708258,0.000761986,0.002378859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002909478,"threshold_uncertainty_score":0.015387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03674720432760291,"score_gpt":0.2681822405872508,"score_spread":0.2314350362596478,"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."}}