{"id":"W4237782444","doi":"10.32920/ryerson.14645553.v1","title":"Design and Build of an Anthropomorphic Active Vision System","year":2021,"lang":"en","type":"preprint","venue":"","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Inertial measurement unit; Vergence (optics); Convolutional neural network; Human visual system model; Machine vision; Systems design; Kalman filter; Active vision; Human–computer interaction; Image (mathematics)","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":[0.00009981744,0.0001883726,0.0003310085,0.00007387054,0.00002366507,0.00005650678,0.00009965337,0.0001540769,0.00003789211],"category_scores_gemma":[0.000006601235,0.0001810688,0.00003697031,0.00006679317,0.00005126883,0.00007619894,0.000121721,0.0002594856,0.000001907435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005168519,"about_ca_system_score_gemma":0.00002790778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001343387,"about_ca_topic_score_gemma":0.000006445047,"domain_scores_codex":[0.9992414,0.00005735947,0.0001915456,0.0002554786,0.0001279657,0.0001262904],"domain_scores_gemma":[0.9994484,0.00004185436,0.00004002941,0.0003368345,0.00007252977,0.00006042037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007728901,0.0001920225,0.0001312394,0.008664731,0.0007040683,0.0002888479,0.005381118,0.7631006,0.1505515,0.0005895384,0.0008900181,0.06942904],"study_design_scores_gemma":[0.0002481317,0.00005654627,0.0007747078,0.00107346,0.00007446112,0.00006209737,0.002998056,0.8065716,0.1876348,0.00003624952,0.00006227825,0.0004075853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8721353,0.0006947548,0.1235326,0.00002139368,0.0005828805,0.0002723486,0.00001298011,0.0004551273,0.00229267],"genre_scores_gemma":[0.9859284,0.0001241421,0.01380259,0.000004084586,0.00004177888,0.000006065698,0.00001960503,0.00003811662,0.00003518091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1137932,"threshold_uncertainty_score":0.7383773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200169554733112,"score_gpt":0.241171244543613,"score_spread":0.2291695489962819,"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."}}