{"id":"W2887879157","doi":"10.18653/v1/w18-5434","title":"Learning Explanations from Language Data","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Explainable Artificial Intelligence (XAI)","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; Linguistics; Psychology; Natural language processing; Cognitive psychology; Data science; Cognitive science; Philosophy","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":[0.001237863,0.000974319,0.0005101961,0.002090183,0.0005217633,0.001455726,0.00158286,0.001178514,0.004606895],"category_scores_gemma":[0.01389767,0.0003795823,0.001434302,0.001464777,0.00123747,0.00392705,0.001965753,0.002524213,0.0007367107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007613156,"about_ca_system_score_gemma":0.0007318544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001378617,"about_ca_topic_score_gemma":0.002799546,"domain_scores_codex":[0.9989517,0.000405707,0.00005486215,0.0002928408,0.0002353776,0.00005938493],"domain_scores_gemma":[0.9945537,0.003741672,0.0003298102,0.0009171492,0.0003390939,0.000118531],"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":[0.0003179214,0.0002276102,0.01201224,0.0008821318,0.0005112479,0.00103867,0.00170751,0.07609445,0.006884928,0.3681627,0.02794567,0.5042149],"study_design_scores_gemma":[0.0000445551,0.00004578763,0.001533848,0.0001297217,0.00007402866,0.0001748555,0.0001583046,0.323587,0.003869864,0.6573117,0.01303734,0.00003306236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04975472,0.001290357,0.9356298,0.003734737,0.0002207981,0.0001006702,0.002407408,0.002131308,0.00473026],"genre_scores_gemma":[0.6901094,0.001302672,0.2952605,0.0007361948,0.0003414762,0.0002159373,0.007547101,0.0003175196,0.004169233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004606895,"threshold_uncertainty_score":0.01541162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09718035733699655,"score_gpt":0.3463604548073858,"score_spread":0.2491800974703892,"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."}}