{"id":"W6888445825","doi":"10.21227/sfay-xp83","title":"Data and Code for Paper – Improving Vis Deisgn for Effective Multi-objective Decision Making","year":2020,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Development Research Centre","funders":"","keywords":"Radar chart; Visualization; Chart; Quality (philosophy); Data visualization; Scatter plot; Decision tree; Plot (graphics); Code (set theory)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00238688,0.001264236,0.001635383,0.0004437872,0.0005852484,0.0004331004,0.003108485,0.000785249,0.00003427311],"category_scores_gemma":[0.007266998,0.001249491,0.0002376961,0.000419286,0.0002379878,0.001773689,0.00245481,0.0009049168,0.0006349159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004155135,"about_ca_system_score_gemma":0.0005098171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002061892,"about_ca_topic_score_gemma":0.006442169,"domain_scores_codex":[0.9929357,0.0001702501,0.00114826,0.003871607,0.0007713776,0.001102855],"domain_scores_gemma":[0.9894585,0.003840874,0.001315588,0.004590581,0.000433264,0.0003612139],"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":[0.002105211,0.0001893923,0.00002304029,0.001160173,0.0005878125,0.00008358173,0.00005177315,0.000008766699,0.001552219,0.000001162134,0.9741246,0.0201123],"study_design_scores_gemma":[0.00393827,0.0004554358,0.0002324807,0.000722268,0.001760083,0.00007408979,0.00008709278,0.008304677,0.0002846176,0.00005970209,0.9826983,0.001382999],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004954008,0.0002329596,0.08531354,0.00001464164,0.001439843,0.009053959,0.9037009,0.0001917303,0.000002819075],"genre_scores_gemma":[0.0001824076,0.0000628998,0.04007273,0.0005046778,0.001178302,0.002043771,0.9554769,0.0004683573,0.00000999839],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05177589,"threshold_uncertainty_score":0.9989955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05576740288103518,"score_gpt":0.3683002303843906,"score_spread":0.3125328275033554,"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."}}