{"id":"W32031805","doi":"10.1007/978-3-319-06483-3_14","title":"A Consensus Approach for Annotation Projection in an Advanced Dialog Context","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Nuance Communications (Canada); Université de Montréal","funders":"","keywords":"Computer science; Annotation; Dialog box; Projection (relational algebra); Exploit; Context (archaeology); Universalization; Artificial intelligence; Process (computing); Natural language processing; World Wide Web; Programming language; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.008826677,0.001391905,0.001969623,0.002951479,0.004162404,0.004916458,0.004951713,0.003538491,0.01152194],"category_scores_gemma":[0.02056943,0.00178884,0.002594053,0.003205301,0.00291654,0.01031152,0.0110624,0.004338166,0.00419674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001603371,"about_ca_system_score_gemma":0.004743578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006470536,"about_ca_topic_score_gemma":0.007467748,"domain_scores_codex":[0.9896187,0.003910987,0.0008746827,0.002575817,0.002431934,0.0005878814],"domain_scores_gemma":[0.9870863,0.005456393,0.000351156,0.002636492,0.003906014,0.0005635772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005725328,0.000292714,0.0009567622,0.0006600274,0.0001867775,0.0006645421,0.00432598,0.04526991,0.01549855,0.530236,0.01579558,0.3855406],"study_design_scores_gemma":[0.00005230061,0.0001260628,0.0002865866,0.0001528839,0.000128228,0.000233917,0.001098369,0.4906816,0.01393259,0.471135,0.02205388,0.0001186377],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001692805,0.00006989558,0.9952099,0.0001451807,0.00005167966,0.0001088574,0.00008935579,0.0006939403,0.001938382],"genre_scores_gemma":[0.09760063,0.0001507997,0.8944666,0.0001589169,0.00009804605,0.0004932301,0.0007180998,0.0004750092,0.005838642],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01152194,"threshold_uncertainty_score":0.04668045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115073581766926,"score_gpt":0.2822775895014908,"score_spread":0.2611268536838215,"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."}}