{"id":"W2796683355","doi":"10.1145/3183568","title":"Usertesting Without the User","year":2018,"lang":"en","type":"article","venue":"Computers in entertainment","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"University of Ontario Institute of Technology","keywords":"Computer science; Proxy (statistics); Process (computing); Human–computer interaction; Population; Human intelligence; Artificial intelligence; Cognition; Data science; Machine learning; Psychology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02317452,0.001143836,0.001250522,0.00112604,0.001045615,0.003141819,0.00231192,0.001262326,0.01593652],"category_scores_gemma":[0.06334341,0.0006044708,0.0006473307,0.0005573537,0.001822722,0.00300004,0.003208916,0.001202318,0.00590212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008803818,"about_ca_system_score_gemma":0.001171902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007776305,"about_ca_topic_score_gemma":0.001419845,"domain_scores_codex":[0.9763626,0.01698267,0.001085965,0.002307737,0.002648797,0.0006122201],"domain_scores_gemma":[0.915917,0.03758701,0.003213586,0.03069619,0.009398542,0.003187749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006662331,0.007636208,0.06453877,0.001155991,0.0003713289,0.0007268922,0.02428575,0.0111144,0.06258913,0.01806945,0.01986371,0.782986],"study_design_scores_gemma":[0.003132747,0.03332846,0.1151528,0.001323777,0.0006492383,0.002917635,0.01773214,0.1562822,0.1318423,0.07209188,0.4645979,0.0009488607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5966491,0.0002878545,0.3515423,0.0009575725,0.0002924263,0.005679152,0.0008390428,0.003103375,0.04064929],"genre_scores_gemma":[0.8256483,0.0001041617,0.1509255,0.0006517151,0.00007824501,0.007727504,0.0007695025,0.0005568129,0.01353828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02317452,"threshold_uncertainty_score":0.1225601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02711012667811259,"score_gpt":0.2887080969848481,"score_spread":0.2615979703067355,"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."}}