{"id":"W2921869280","doi":"10.1145/3294109.3295627","title":"You say Potato, I say Po-Data","year":2019,"lang":"en","type":"article","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Visualization; Computer science; Leverage (statistics); Annotation; Human–computer interaction; Data visualization; Block (permutation group theory); Information visualization; Fidelity; Usability; World Wide Web; Computer graphics (images); Multimedia; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002118925,0.00007091794,0.00008602579,0.00005360602,0.00003258426,0.0002126254,0.001799165,0.00002580382,0.0007389658],"category_scores_gemma":[0.00003033747,0.00005718168,0.00001941916,0.0002856873,0.00001128503,0.0007528082,0.0008573799,0.00004415536,0.003600093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006056332,"about_ca_system_score_gemma":0.00004509918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002201808,"about_ca_topic_score_gemma":0.00001003951,"domain_scores_codex":[0.999147,0.00002338194,0.0001326896,0.0003373901,0.0002053522,0.0001541745],"domain_scores_gemma":[0.9983043,0.00002732044,0.00003600983,0.001521509,0.00003915454,0.00007172322],"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":[9.904334e-7,0.00007722573,0.00353219,0.00001202005,0.00001791634,0.000005575612,0.0001270554,0.00003738957,0.0001659682,0.6971008,0.2799954,0.01892753],"study_design_scores_gemma":[0.0002541678,0.0000280785,0.00102009,0.000008363608,0.000004032563,0.000004389401,0.00003970127,0.5386345,0.0004015102,0.002073677,0.4573357,0.0001957849],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0008830479,0.00002813236,0.9067776,0.003675889,0.0004194951,0.00008377996,0.00002331785,0.0002352502,0.08787356],"genre_scores_gemma":[0.4762616,0.00009196757,0.1362221,0.05465221,0.000290328,0.000003019444,0.0008983554,0.0000443626,0.331536],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7705554,"threshold_uncertainty_score":0.9971757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03463846551360285,"score_gpt":0.3087285460835585,"score_spread":0.2740900805699557,"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."}}