{"id":"W4389520223","doi":"10.18653/v1/2023.emnlp-tutorial.1","title":"NLP+Vis: NLP Meets Visualization","year":2023,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Leverage (statistics); Visualization; Artificial intelligence; Intersection (aeronautics); Natural language processing; Modalities; Focus (optics); Deep learning","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002188905,0.00007718287,0.00007961666,0.0001801197,0.00009007075,0.0002261335,0.0005069151,0.00003394912,0.0001332171],"category_scores_gemma":[0.00006569891,0.00006860482,0.00003127847,0.001496289,0.00001465023,0.0005046508,0.0002385852,0.0000266473,0.001920864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001272033,"about_ca_system_score_gemma":0.00003209587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009203382,"about_ca_topic_score_gemma":0.000007203984,"domain_scores_codex":[0.9991122,0.00003410927,0.0001663703,0.0002431397,0.000262777,0.0001813868],"domain_scores_gemma":[0.9994196,0.00003173001,0.00004097346,0.0003605715,0.00007225402,0.00007490091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[2.957748e-7,0.00002469073,0.0002453786,0.00000712187,0.000006267755,0.000005619892,0.000173574,0.0001172599,0.0001762263,0.8935639,0.1005778,0.00510184],"study_design_scores_gemma":[0.0001396125,0.00002182621,0.0008183564,0.000008205824,0.000003005964,0.000001898705,0.00004756798,0.8071747,0.001230265,0.002134176,0.1882821,0.0001382674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005848772,0.000009955633,0.9821377,0.001718718,0.0002944315,0.00006335178,0.000003341039,0.001201697,0.0139859],"genre_scores_gemma":[0.9264469,0.0002784863,0.01624134,0.00824063,0.0002674014,0.0000188887,0.0004492168,0.00004576435,0.04801143],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9658964,"threshold_uncertainty_score":0.9988562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03612026689251242,"score_gpt":0.3393710046578898,"score_spread":0.3032507377653774,"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."}}