{"id":"W2794729851","doi":"10.1016/j.infsof.2018.03.001","title":"Special section on Visual Analytics in Software Engineering","year":2018,"lang":"en","type":"article","venue":"Information and Software Technology","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Visualization; Visual analytics; Process (computing); Context (archaeology); Data science; Information visualization; Data visualization; Human–computer interaction; Analytics; Creative visualization; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001197984,0.00009605123,0.0001075102,0.0008801434,0.00007432722,0.0001140813,0.0002322737,0.0001488859,0.00002167049],"category_scores_gemma":[0.000460013,0.00009718,0.00001547333,0.0009283386,0.00005581833,0.0009033307,0.0001309425,0.000142034,0.00009654617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004896263,"about_ca_system_score_gemma":0.00003190463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003929924,"about_ca_topic_score_gemma":0.00002029646,"domain_scores_codex":[0.9993141,0.00000707212,0.0002603327,0.0001219836,0.0001324695,0.0001640902],"domain_scores_gemma":[0.9995636,0.00003104441,0.00007594093,0.0001921594,0.00009938074,0.00003790137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002156869,0.0001160942,0.04171399,0.00006920615,0.00002718553,0.00001024478,0.001577045,0.0008955877,0.00001788484,0.2914153,0.01381582,0.6503201],"study_design_scores_gemma":[0.001590328,0.0008521109,0.02323943,0.0001153308,0.000009406675,0.00007328741,0.0002524508,0.417614,0.001330208,0.00301228,0.5512151,0.0006960828],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02737924,0.000004677805,0.9702212,0.0003620265,0.000851322,0.00008535683,0.000004574359,0.0007458593,0.0003457687],"genre_scores_gemma":[0.8737184,0.0001017553,0.1194538,0.00380008,0.002523871,0.00002650911,0.0001321528,0.00002538381,0.0002179437],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8507673,"threshold_uncertainty_score":0.3962885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008342315570618404,"score_gpt":0.2514719885727999,"score_spread":0.2431296730021815,"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."}}