{"id":"W4403896196","doi":"10.1111/cgf.15266","title":"Natural Language Generation for Visualizations: State of the Art, Challenges and Future Directions","year":2024,"lang":"en","type":"article","venue":"Computer Graphics Forum","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre International de Recherche sur le Cancer","keywords":"Computer science; State (computer science); Visualization; Natural (archaeology); Computer graphics (images); Natural language generation; Human–computer interaction; Natural language; Artificial intelligence; Programming language; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000137049,0.00008841912,0.00008739235,0.0001447673,0.0001390325,0.0001786017,0.000262708,0.00002990772,7.581945e-7],"category_scores_gemma":[0.000007780935,0.00006375217,0.00007156399,0.0004141715,0.00004392825,0.000310063,0.000152876,0.00006884978,0.000001132976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006693076,"about_ca_system_score_gemma":0.00002802788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001208636,"about_ca_topic_score_gemma":0.00006624505,"domain_scores_codex":[0.9993255,0.00003820429,0.0001589112,0.0002303712,0.0001276246,0.0001194626],"domain_scores_gemma":[0.9995121,0.00005352263,0.00004558351,0.000271126,0.0000884285,0.000029234],"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":[4.735399e-7,0.00001967812,0.00001298433,0.00006139353,0.00003193221,5.406336e-7,0.001377659,0.00001785901,0.00007873244,0.8501579,0.007250864,0.14099],"study_design_scores_gemma":[0.00007221217,0.00002620839,0.0002437559,0.00002802238,0.000009170366,0.000005825708,0.0000322783,0.7926966,0.0001843273,0.003769042,0.2028576,0.00007493605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008742739,0.02128062,0.9690277,0.006016226,0.002336912,0.0002135894,0.00004076304,0.0001549285,0.00005498337],"genre_scores_gemma":[0.886152,0.04621913,0.05513187,0.006164826,0.003271538,0.0001276956,0.000561003,0.0001103684,0.00226159],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9138958,"threshold_uncertainty_score":0.2599738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966146682931232,"score_gpt":0.2910691527554301,"score_spread":0.2714076859261178,"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."}}