{"id":"W4392752805","doi":"10.6339/24-jds1121","title":"Testing Perceptual Accuracy in a U.S. General Population Survey Using Stacked Bar Charts","year":2024,"lang":"en","type":"article","venue":"Journal of Data Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bar chart; Visualization; Perception; Computer science; Bar (unit); Data visualization; Information visualization; Pie chart; Population; Key (lock); Data science; Survey data collection; Human–computer interaction; Data mining; Psychology; Statistics; Mathematics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01749553,0.0004185706,0.0004350253,0.001892739,0.0006702736,0.001716636,0.000976623,0.001201784,0.003207192],"category_scores_gemma":[0.102006,0.0003640951,0.001109857,0.002226591,0.001160567,0.001995681,0.001941306,0.001107812,0.0006912305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005479188,"about_ca_system_score_gemma":0.0006374692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01337785,"about_ca_topic_score_gemma":0.01210647,"domain_scores_codex":[0.9859529,0.008045066,0.0013176,0.001672993,0.002356689,0.0006547995],"domain_scores_gemma":[0.9104167,0.05635109,0.01191011,0.008478437,0.01089179,0.0019519],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000331002,0.000355607,0.9740058,0.00008113788,0.0001786514,0.00007226918,0.004626767,0.001239167,0.0004011232,0.000513787,0.002323467,0.01587127],"study_design_scores_gemma":[0.00003926989,0.0009935485,0.9801958,0.00007132401,0.00008024866,0.0001182716,0.006688212,0.008097414,0.000637668,0.0008950904,0.002136333,0.00004686625],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927644,0.00006098879,0.003422395,0.000283957,0.00004241732,0.00009378878,0.0009103972,0.00008002602,0.002341741],"genre_scores_gemma":[0.9965557,0.00004794452,0.002103287,0.0001318019,0.00001638788,0.0001344,0.0007566457,0.00001267345,0.0002412038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9825045,"threshold_uncertainty_score":0.09252632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2466232187591786,"score_gpt":0.4300851825046271,"score_spread":0.1834619637454485,"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."}}