{"id":"W2940471369","doi":"10.4230/dagrep.8.10.127","title":"Data Physicalization (Dagstuhl Seminar 18441)","year":2019,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Sports Science and Education","field":"Arts and Humanities","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bauhaus-Universität Weimar; Monash University; University of Lethbridge; Julius-Maximilians-Universität Würzburg; Microsoft Research; Carnegie Mellon University; University of Minnesota","keywords":"Environmental science; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000529953,0.000308039,0.000344895,0.0001953029,0.0004888589,0.0006803166,0.001063684,0.0001044038,0.00145405],"category_scores_gemma":[0.00005674266,0.0002631408,0.0001259652,0.0001350895,0.0002104084,0.003623581,0.000282475,0.0002205069,0.001881864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008441197,"about_ca_system_score_gemma":0.0001109792,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007483879,"about_ca_topic_score_gemma":0.0001114356,"domain_scores_codex":[0.9977373,0.00001592284,0.0007817305,0.0003466663,0.000511035,0.0006073614],"domain_scores_gemma":[0.9978439,0.00007395323,0.0003962358,0.001246981,0.0002942427,0.0001447515],"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":[0.0002116888,0.001622698,0.02510404,0.001558534,0.0002974672,0.000003254146,0.2683416,0.0003199104,0.000245824,0.2184923,0.460245,0.02355768],"study_design_scores_gemma":[0.0008454454,0.0001531708,0.0006191512,0.0001166427,0.00004965141,0.000007258879,0.01877018,0.02143668,0.0001346172,0.0006041809,0.9568157,0.0004473567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8859233,0.00006760366,0.001962269,0.0008656977,0.006465674,0.002076079,0.002299232,0.0003493243,0.09999087],"genre_scores_gemma":[0.9759569,0.00003503992,0.0007736947,0.001783453,0.001238308,0.00006624772,0.007263383,0.00005596417,0.01282707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4965706,"threshold_uncertainty_score":0.9999821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05422155330270124,"score_gpt":0.2809444661312092,"score_spread":0.2267229128285079,"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."}}