{"id":"W3202884280","doi":"10.1177/25152459211045334","title":"Doing Better Data Visualization","year":2021,"lang":"en","type":"article","venue":"Advances in Methods and Practices in Psychological Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Visualization; Computer science; Data science; Data visualization; Focus (optics); Information visualization; Code (set theory); Creative visualization; World Wide Web; Human–computer interaction; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"opus","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006213713,0.0000928232,0.0001486309,0.0001415929,0.0001201651,0.0004232375,0.001563089,0.00004774955,0.00003308409],"category_scores_gemma":[0.004610827,0.00007492907,0.000009261178,0.002741871,0.0002791133,0.006751124,0.001041023,0.0001885435,0.000003808594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001765673,"about_ca_system_score_gemma":0.00004105084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004971149,"about_ca_topic_score_gemma":0.00002724755,"domain_scores_codex":[0.9974781,0.000670418,0.0003066834,0.0009823209,0.0002963241,0.0002661535],"domain_scores_gemma":[0.9978304,0.0009298312,0.0002585242,0.00083954,0.00006697618,0.00007472422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003367923,0.0001278295,0.009165596,0.000008788536,7.161953e-7,0.00003810958,0.0001326158,0.00005077789,0.001222963,0.1286301,0.00002428065,0.8605949],"study_design_scores_gemma":[0.000610646,0.0001046592,0.02316003,0.00008063451,0.000006005343,0.0001153812,0.0003271052,0.3117509,0.001189105,0.0988759,0.5633238,0.0004558236],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00214548,0.002040294,0.984531,0.001343049,0.0004085955,0.00005235712,0.000001647155,0.00002774919,0.009449763],"genre_scores_gemma":[0.02998099,0.005737862,0.9617992,0.002417061,0.00002972241,0.000003246069,0.000007091079,0.000002519659,0.00002228374],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.860139,"threshold_uncertainty_score":0.5519924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1328647568179597,"score_gpt":0.6140051293640173,"score_spread":0.4811403725460576,"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."}}