{"id":"W2996259875","doi":"","title":"Democratisation of Usable Machine Learning in Computer Vision","year":2019,"lang":"en","type":"article","venue":"Research Portal (Queen's University Belfast)","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"USable; Democratization; Computer science; Artificial intelligence; Machine learning; Human–computer interaction; Multimedia; Political science; Democracy","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":[0.0006709841,0.00009606448,0.0001836965,0.0005037237,0.0001090717,0.0000883645,0.0007176403,0.00006464644,0.0001495332],"category_scores_gemma":[0.00002506596,0.0001048061,0.00004961825,0.0007700355,0.00008256797,0.001936122,0.0008748401,0.0003782022,0.0001940317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008697158,"about_ca_system_score_gemma":0.0001744845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001228082,"about_ca_topic_score_gemma":0.00006261977,"domain_scores_codex":[0.9984568,0.0001908277,0.0001750467,0.0003913099,0.0004244454,0.0003615427],"domain_scores_gemma":[0.9991069,0.0001558131,0.00007836799,0.0003895922,0.0001472178,0.000122132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002519803,0.001087177,0.5633966,0.0003134583,0.00008248075,0.0009383863,0.001339757,0.009885487,0.0009166143,0.3246346,0.007946277,0.08920719],"study_design_scores_gemma":[0.005751591,0.00385199,0.3329048,0.0005532617,0.00001039239,0.00003747285,0.000982451,0.5652785,0.002804245,0.005414616,0.0811807,0.001229911],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9049415,0.00001524964,0.04910241,0.001493621,0.0001406523,0.0005150259,0.00002417693,0.0001080724,0.04365931],"genre_scores_gemma":[0.9927418,0.00002902504,0.003709962,0.00001792027,0.00001450525,2.28971e-7,0.00004561559,0.000005497503,0.003435444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.555393,"threshold_uncertainty_score":0.427387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02096037916967674,"score_gpt":0.2625800436945431,"score_spread":0.2416196645248663,"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."}}