{"id":"W2298580697","doi":"10.5206/tjr.2016.1.4.5","title":"Accessible and Interactive","year":2016,"lang":"en","type":"article","venue":"Transitional justice review","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Visualization; Data science; Data visualization; Information visualization; Geovisualization; Graphics; Data mining; Information retrieval; Computer graphics (images)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009324943,0.001295795,0.001118093,0.006049124,0.001655311,0.007831172,0.002913857,0.001671999,0.1662325],"category_scores_gemma":[0.04607117,0.0009196185,0.001725063,0.009632865,0.001569523,0.009186825,0.009704869,0.002000332,0.06328151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068188,"about_ca_system_score_gemma":0.002542215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003071164,"about_ca_topic_score_gemma":0.004107184,"domain_scores_codex":[0.9912302,0.003932266,0.0007018194,0.001090528,0.002623707,0.0004215125],"domain_scores_gemma":[0.9674793,0.01679211,0.001246742,0.009142851,0.004284921,0.001054029],"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":[0.0003313525,0.0001405602,0.001431689,0.002067559,0.0001122994,0.0003507689,0.006418672,0.001185826,0.002704605,0.07546975,0.4734708,0.4363161],"study_design_scores_gemma":[0.00004713665,0.00003128324,0.00126574,0.0004905426,0.00002445718,0.0001931282,0.0009827898,0.000912691,0.0007439831,0.02772016,0.9675395,0.00004855535],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.007326385,0.005790276,0.4845456,0.007219765,0.001979274,0.001774162,0.03946798,0.06570656,0.38619],"genre_scores_gemma":[0.1265879,0.0112181,0.6081402,0.00452706,0.002398398,0.007876164,0.04614709,0.02280062,0.1703046],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1662325,"threshold_uncertainty_score":0.5561032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01870410942815201,"score_gpt":0.3023357617347819,"score_spread":0.2836316523066299,"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."}}