{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001114715,0.0001308158,0.0001470623,0.00007964572,0.0001231642,0.0002653699,0.002823529,0.00003930623,0.00003144861],"category_scores_gemma":[0.000158606,0.00009766769,0.000108991,0.0003710636,0.00002906486,0.0008594259,0.001296309,0.0001838116,0.0000819932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003189182,"about_ca_system_score_gemma":0.000009719228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003505883,"about_ca_topic_score_gemma":2.669762e-7,"domain_scores_codex":[0.9989312,0.000008556987,0.0002805431,0.0003289998,0.0003124343,0.0001383168],"domain_scores_gemma":[0.9990436,0.00003325892,0.0002712492,0.0003876021,0.0001959453,0.00006834355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005836501,0.0004477516,0.001674312,0.0002592828,0.000146163,0.000001940642,0.006424387,0.0004372428,0.05853164,0.450473,0.4394329,0.04211295],"study_design_scores_gemma":[0.001232893,0.001029032,0.005212755,0.0004508242,0.00005422702,0.00003049682,0.0002532894,0.5877526,0.261151,0.01928219,0.1227824,0.0007682358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6005072,0.00003002217,0.2665168,0.09279153,0.005153826,0.001108967,0.00001723779,0.001526995,0.03234744],"genre_scores_gemma":[0.982251,0.000003355903,0.01116279,0.005890709,0.0004272659,0.000004078666,0.000002738449,0.00001324034,0.0002448419],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5873154,"threshold_uncertainty_score":0.5246866,"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."}}