{"id":"W2894646045","doi":"10.1101/434944","title":"USE: An integrative suite for temporally-precise psychophysical experiments in virtual environments for human, nonhuman, and artificially intelligent agents","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Suite; Set (abstract data type); Software; Key (lock); Variety (cybernetics); Reinforcement learning; Video game; Virtual reality","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":[0.003122093,0.001532124,0.0009488761,0.001450902,0.0004107677,0.001003293,0.002522823,0.0007452158,0.0122834],"category_scores_gemma":[0.003920229,0.0008598075,0.001041379,0.0004714448,0.000741337,0.001013722,0.003090554,0.0008995582,0.002565894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004211359,"about_ca_system_score_gemma":0.0006464669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003513944,"about_ca_topic_score_gemma":0.0006767681,"domain_scores_codex":[0.9983249,0.000527475,0.000132107,0.0002188187,0.0006723937,0.000124289],"domain_scores_gemma":[0.9966342,0.001362589,0.0002164391,0.001105649,0.0003545438,0.000326584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002410847,0.001779438,0.006151851,0.001307955,0.0005584697,0.0005385608,0.001062907,0.02111974,0.6309868,0.0109035,0.03097841,0.2922016],"study_design_scores_gemma":[0.001239043,0.005350767,0.04343851,0.0003384299,0.0003132161,0.001939376,0.0003475257,0.2249925,0.5043765,0.01820085,0.1987763,0.0006869878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05185756,0.0003622403,0.849147,0.0001273397,0.0001331657,0.002350479,0.003514774,0.08355903,0.008948364],"genre_scores_gemma":[0.1583929,0.0003190077,0.807995,0.0002474547,0.00007164091,0.006986186,0.004807834,0.01429977,0.006880244],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0122834,"threshold_uncertainty_score":0.0410921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0678556994613429,"score_gpt":0.3185268023793667,"score_spread":0.2506711029180238,"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."}}