{"id":"W3082046364","doi":"10.1109/beliv51497.2020.00016","title":"Data-First Visualization Design Studies","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Transferability; Process (computing); Data science; Visualization; Design process; Data visualization; Adaptation (eye); Data mining; Engineering; Machine learning; Work in process; Programming language","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":[0.1198686,0.002088008,0.001525754,0.005092949,0.003262371,0.01204526,0.004304733,0.003806761,0.008939209],"category_scores_gemma":[0.1537543,0.001964426,0.002384782,0.003048568,0.005440521,0.01034721,0.008508382,0.004711839,0.00182808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005934095,"about_ca_system_score_gemma":0.007461152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008122558,"about_ca_topic_score_gemma":0.0009747846,"domain_scores_codex":[0.8529921,0.1173272,0.007632598,0.00635739,0.01323999,0.002450736],"domain_scores_gemma":[0.7177397,0.2030052,0.01176729,0.03580756,0.02793485,0.003745275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001489513,0.001380284,0.01264713,0.01345801,0.0004374555,0.0009444903,0.07574802,0.009194965,0.02099296,0.519079,0.0126673,0.3319608],"study_design_scores_gemma":[0.00135327,0.003981554,0.005602711,0.008098453,0.0004327613,0.001223964,0.02360512,0.01981653,0.05295425,0.3364576,0.5460705,0.0004032225],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03333021,0.00170343,0.9263401,0.003909253,0.0005220996,0.01068774,0.0009538626,0.000836432,0.02171693],"genre_scores_gemma":[0.1544506,0.0007987312,0.8203256,0.001351286,0.0001008071,0.01785455,0.0006285924,0.0004448051,0.004045041],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1198686,"threshold_uncertainty_score":0.6339335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3454013949793777,"score_gpt":0.4320852758923909,"score_spread":0.08668388091301321,"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."}}