{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001819354,0.00005626686,0.00008450668,0.00007899933,0.0001234408,0.00001473745,0.0001567788,0.00004539796,9.559526e-7],"category_scores_gemma":[0.00001276466,0.00005201102,0.000007775544,0.0002120788,0.0001897193,0.0001653784,0.00006663772,0.0000746396,2.127263e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004407822,"about_ca_system_score_gemma":0.00003131057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002990552,"about_ca_topic_score_gemma":0.000003123524,"domain_scores_codex":[0.9995124,0.00005025151,0.0001370237,0.0001633862,0.00006759376,0.00006936679],"domain_scores_gemma":[0.9995304,0.0001195966,0.00006245029,0.0002142482,0.00004813449,0.00002519303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001005554,0.00002698921,0.007870097,0.00002540457,0.000001679281,4.21464e-7,0.0005663304,0.001442636,0.004352503,0.9765158,0.00000101185,0.009187085],"study_design_scores_gemma":[0.0004593698,0.00002870792,0.009932157,0.00006278594,0.000008928555,0.00001730821,0.0002404934,0.2613573,0.01791041,0.7096568,0.0001193187,0.0002063983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2944072,0.000195919,0.7051371,0.00004042422,0.000008137087,0.00008913351,8.705728e-7,0.00001835249,0.0001028871],"genre_scores_gemma":[0.983225,0.0000820407,0.01661599,0.00003495785,0.000008031001,0.00001727933,0.000002931633,0.000002168972,0.00001160403],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6888179,"threshold_uncertainty_score":0.2120948,"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."}}