{"id":"W2397199043","doi":"","title":"Summarizing with Roget's and with FrameNet.","year":2009,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"FrameNet; Computer science; Pairwise comparison; Natural language processing; Semantic similarity; Thesaurus; Information retrieval; Sentence; Artificial intelligence; Graph; Similarity (geometry); Semantic property; Task (project management); Image (mathematics); Theoretical computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.005395959,0.001582938,0.001266056,0.002609104,0.001161967,0.002564014,0.001895579,0.002083737,0.01487258],"category_scores_gemma":[0.03028787,0.0007184302,0.001237351,0.002023289,0.0005581593,0.005590057,0.002191008,0.001712698,0.00596361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009825844,"about_ca_system_score_gemma":0.00145145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0106726,"about_ca_topic_score_gemma":0.01743253,"domain_scores_codex":[0.9968492,0.00128525,0.0002621918,0.0007992361,0.0005484694,0.0002557335],"domain_scores_gemma":[0.990184,0.004700918,0.0002900105,0.002017569,0.002281752,0.0005257886],"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":[0.004213795,0.0009478683,0.005986535,0.003205442,0.0006928619,0.0006792701,0.006088956,0.01928161,0.01509735,0.01162756,0.3311598,0.601019],"study_design_scores_gemma":[0.001999421,0.003127118,0.02053867,0.0004623593,0.0008303761,0.0007880537,0.004246342,0.3950261,0.04687556,0.03518509,0.4904867,0.0004342419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2927749,0.002567595,0.3299654,0.003083449,0.003513835,0.003232803,0.05437418,0.2493479,0.06113983],"genre_scores_gemma":[0.397932,0.0003796116,0.4505084,0.0005593824,0.0004034944,0.001792253,0.1159094,0.009537503,0.02297794],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01487258,"threshold_uncertainty_score":0.04975373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003971854845075968,"score_gpt":0.2299566432220285,"score_spread":0.2259847883769525,"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."}}