{"id":"W7111786345","doi":"","title":"METIS: Multiple Extraction Techniques for Informative Sentences","year":2004,"lang":"en","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pattern recognition (psychology); Feature extraction; Matching (statistics); Extraction (chemistry); Class (philosophy)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002714534,0.002719632,0.00132642,0.006758366,0.001565612,0.002415873,0.001731859,0.001361331,0.01592105],"category_scores_gemma":[0.009589224,0.001268371,0.001979661,0.004729173,0.0004516945,0.003352755,0.002552674,0.002286425,0.009485637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005964806,"about_ca_system_score_gemma":0.001717726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001098187,"about_ca_topic_score_gemma":0.002918343,"domain_scores_codex":[0.9974169,0.0007527916,0.0003869374,0.0005281786,0.0007511745,0.0001639911],"domain_scores_gemma":[0.9952605,0.002339018,0.0004997584,0.0006235987,0.001150122,0.000127027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006289392,0.0001920201,0.002085978,0.001952063,0.0003569086,0.0005740013,0.001069979,0.001827202,0.06505733,0.01118457,0.1014505,0.8136205],"study_design_scores_gemma":[0.0005922645,0.0009482153,0.01247112,0.0007306741,0.001573787,0.00303346,0.002030667,0.2826614,0.2011004,0.05984056,0.4346184,0.0003990605],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01060625,0.0009212125,0.9293733,0.000519444,0.0004504975,0.0008234764,0.01812234,0.03542037,0.003763041],"genre_scores_gemma":[0.04978472,0.0004624249,0.9113429,0.0001400071,0.000353609,0.0009554189,0.02877711,0.002807173,0.005376595],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01592105,"threshold_uncertainty_score":0.05326122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1043092021438885,"score_gpt":0.3360963677354666,"score_spread":0.2317871655915781,"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."}}