{"id":"W3095283945","doi":"10.1145/3427323","title":"Flex-ER","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Horizon 2020 Framework Programme","keywords":"FLEX; Computer science; Human–computer interaction; JSON; Visualization; Flexibility (engineering); Debugging; Field (mathematics); Software engineering; Multimedia; World Wide Web; Operating system; Artificial intelligence","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":[0.001541814,0.001395871,0.0005416228,0.0007320358,0.0005098889,0.001770293,0.002337701,0.00133685,0.0800133],"category_scores_gemma":[0.004420802,0.0005491292,0.001087256,0.0005815108,0.0004490157,0.004065293,0.003400023,0.001215985,0.02679959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002543976,"about_ca_system_score_gemma":0.0005424013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006413971,"about_ca_topic_score_gemma":0.0008133759,"domain_scores_codex":[0.9992235,0.0001505809,0.00007488962,0.0001648674,0.0002894074,0.00009671965],"domain_scores_gemma":[0.997779,0.000790842,0.0000853692,0.0008642507,0.000328364,0.0001522061],"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":[0.002253178,0.0007198355,0.002412291,0.002143252,0.00009865974,0.001128138,0.001551243,0.008340454,0.04698614,0.04391211,0.20437,0.6860847],"study_design_scores_gemma":[0.0004426143,0.0007828481,0.003502221,0.0003771103,0.00008935433,0.00263514,0.0005305969,0.04091015,0.05816623,0.03473278,0.8575775,0.0002534446],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03240552,0.001393544,0.6275808,0.0009885879,0.0004960287,0.0008887594,0.01123716,0.2034017,0.1216079],"genre_scores_gemma":[0.2168243,0.002007389,0.5458342,0.001725901,0.0001921384,0.00208233,0.03095369,0.03114378,0.1692363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0800133,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08918782119899336,"score_gpt":0.3476504447671012,"score_spread":0.2584626235681078,"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."}}