{"id":"W3146926538","doi":"10.1109/icse.2012.6227238","title":"WorkItemExplorer: Visualizing software development tasks using an interactive exploration environment","year":2012,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Data exploration; Task (project management); Ask price; Human–computer interaction; Software; Software development; Task management; Visualization; Task analysis; Data visualization; Interactive visualization; Software engineering; Artificial intelligence; Systems engineering; Programming language; Engineering","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":[0.001023291,0.001468518,0.0004810656,0.001673083,0.0005726891,0.002419047,0.001381114,0.001031287,0.01650794],"category_scores_gemma":[0.003133549,0.0007004531,0.0009805397,0.0008320629,0.0004983181,0.00209758,0.003873194,0.001116676,0.00251194],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003114812,"about_ca_system_score_gemma":0.0006658651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003295772,"about_ca_topic_score_gemma":0.00719529,"domain_scores_codex":[0.9995428,0.000156366,0.00002853443,0.00006867725,0.0001227975,0.00008082124],"domain_scores_gemma":[0.9978321,0.001435623,0.00008515363,0.0002592719,0.0001496915,0.0002382335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004101545,0.0009678234,0.0156789,0.003353495,0.0004204833,0.002765979,0.02904832,0.02975715,0.1020582,0.02119837,0.2440176,0.5466321],"study_design_scores_gemma":[0.0008304441,0.0008655857,0.02221793,0.001151411,0.0002769819,0.002188107,0.006709436,0.159449,0.08869848,0.02953844,0.6872023,0.0008718867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08827323,0.001063204,0.7553341,0.001401362,0.0002271746,0.0007569453,0.01348875,0.1043015,0.03515374],"genre_scores_gemma":[0.2716714,0.001261899,0.6937789,0.0005245657,0.00008566174,0.001362971,0.01056671,0.008776197,0.0119717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01650794,"threshold_uncertainty_score":0.0552246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09802627681252768,"score_gpt":0.3253566351947563,"score_spread":0.2273303583822286,"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."}}