{"id":"W3212964142","doi":"10.26615/978-954-452-072-4_183","title":"AutoChart: A Dataset for Chart-to-Text Generation Task","year":2021,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science; Task (project management); Chart; Data science; Natural language processing; Artificial intelligence; Information retrieval; Engineering; Systems engineering","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":[0.0009907736,0.001270146,0.0004550259,0.003656503,0.0008891806,0.001042227,0.001719891,0.002022888,0.008472155],"category_scores_gemma":[0.007467921,0.0002519041,0.0008831447,0.003199528,0.0004067993,0.001415729,0.001101684,0.001336755,0.006661089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225536,"about_ca_system_score_gemma":0.001984743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009721459,"about_ca_topic_score_gemma":0.02268955,"domain_scores_codex":[0.9988518,0.0002507719,0.0001804192,0.0003080482,0.0003320313,0.00007700175],"domain_scores_gemma":[0.9949571,0.00227334,0.0004077184,0.0008332373,0.001185525,0.0003430666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006444186,0.0007358025,0.008416928,0.002430832,0.00008566344,0.0007625341,0.0004742801,0.005715386,0.007576597,0.004245576,0.8668365,0.1020754],"study_design_scores_gemma":[0.0008250371,0.0005304175,0.03094443,0.0004446484,0.0000982882,0.0009157524,0.001096738,0.06078416,0.02083743,0.01057323,0.8727242,0.0002257271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0356712,0.0008923009,0.01553835,0.0008058181,0.0003882977,0.0008525888,0.9206771,0.0185332,0.00664107],"genre_scores_gemma":[0.02689973,0.0002735464,0.03361417,0.0001706317,0.00006121262,0.0009671994,0.935181,0.0004197287,0.00241286],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009721459,"threshold_uncertainty_score":0.02834213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03007901274681364,"score_gpt":0.3094329610311797,"score_spread":0.279353948284366,"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."}}