{"id":"W3094824040","doi":"10.1123/ijspp.2020-0813","title":"Show Me the Data, Jerry! Data Visualization and Transparency","year":2020,"lang":"en","type":"article","venue":"International Journal of Sports Physiology and Performance","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Sport Centre Pacific","funders":"","keywords":"Transparency (behavior); Visualization; Computer science; Artificial intelligence; Computer security","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04236729,0.002018784,0.002260483,0.006443778,0.002448059,0.01464685,0.003290103,0.005577934,0.1771717],"category_scores_gemma":[0.352028,0.001922297,0.003462991,0.00554376,0.003199129,0.0146825,0.00978894,0.009881511,0.06976549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001664673,"about_ca_system_score_gemma":0.005997111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001632923,"about_ca_topic_score_gemma":0.002560007,"domain_scores_codex":[0.9640073,0.02113219,0.003687533,0.002775244,0.007484832,0.0009128734],"domain_scores_gemma":[0.7409973,0.1358694,0.0194337,0.05021648,0.04535129,0.008131912],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005165125,0.00004562001,0.001320303,0.002134119,0.0001552413,0.0001798035,0.001620945,0.0002441869,0.0007688847,0.009055837,0.8993801,0.08457835],"study_design_scores_gemma":[0.0002314511,0.00008444885,0.001653082,0.003135992,0.0001003065,0.0004461303,0.0008938736,0.001840012,0.00188463,0.04182772,0.9477209,0.0001813369],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.006902563,0.01402977,0.2731727,0.3742121,0.07260004,0.00405805,0.08242665,0.09941427,0.07318373],"genre_scores_gemma":[0.115887,0.01186841,0.5771281,0.1179579,0.02029807,0.01356388,0.02424419,0.05134671,0.06770589],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9576327,"threshold_uncertainty_score":0.5926982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05947802969525306,"score_gpt":0.3276387437665449,"score_spread":0.2681607140712918,"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."}}