{"id":"W2250867360","doi":"10.3115/v1/p15-4008","title":"A Web-based Collaborative Evaluation Tool for Automatically Learned Relation Extraction Patterns","year":2015,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Banting and Best Diabetes Centre, University of Toronto; Bundesministerium für Bildung und Forschung","keywords":"Computer science; Preprocessor; Relationship extraction; Dependency (UML); Parsing; Artificial intelligence; Annotation; Dependency grammar; Categorization; Natural language processing; Relation (database); Quality (philosophy); Information extraction; Machine learning; Data mining","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.01440649,0.003038882,0.001995702,0.00940634,0.001492964,0.002781011,0.003321732,0.00238656,0.01333603],"category_scores_gemma":[0.05692672,0.0009102777,0.001135258,0.004936875,0.0005961001,0.005618853,0.003270787,0.001874402,0.006703191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001153259,"about_ca_system_score_gemma":0.001792343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004592575,"about_ca_topic_score_gemma":0.008001552,"domain_scores_codex":[0.9852111,0.005803699,0.001639086,0.002794892,0.004133967,0.0004171381],"domain_scores_gemma":[0.931988,0.04134568,0.002536432,0.01103521,0.01141049,0.001684131],"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":[0.001920988,0.002896373,0.01652871,0.001806459,0.0007502085,0.001031547,0.001914853,0.01479067,0.03376802,0.004232906,0.1525346,0.7678247],"study_design_scores_gemma":[0.0009816389,0.001544821,0.02808698,0.0002227188,0.0003235561,0.001308728,0.001066965,0.8039562,0.06538662,0.01294057,0.08379441,0.0003867887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1054378,0.0006040721,0.6187368,0.0005260696,0.000301868,0.002285749,0.02169444,0.2386055,0.01180784],"genre_scores_gemma":[0.3119866,0.0002107581,0.6004156,0.0003057087,0.0001429158,0.004147344,0.06283367,0.01091571,0.00904163],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01440649,"threshold_uncertainty_score":0.0761897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07510523306801112,"score_gpt":0.3521991237449693,"score_spread":0.2770938906769581,"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."}}