{"id":"W3111123738","doi":"10.3389/frobt.2020.580835","title":"Machine Gaze: Self-Identification Through Play With a computer Vision-Based Projection and Robotics System","year":2020,"lang":"en","type":"article","venue":"Frontiers in Robotics and AI","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Computer science; Gaze; Identity (music); Artificial intelligence; Identification (biology); Human–computer interaction; Face (sociological concept); Computer vision; Aesthetics; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008204636,0.0001287552,0.0001638044,0.00007038856,0.0001312349,0.0001394841,0.00005521017,0.00007028897,0.000003595105],"category_scores_gemma":[0.00001596807,0.000109645,0.0000180612,0.0002436792,0.00006616025,0.0001933321,0.00002068256,0.0001624202,0.000005581303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004125686,"about_ca_system_score_gemma":0.00002429347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009550182,"about_ca_topic_score_gemma":0.000004237603,"domain_scores_codex":[0.9990546,0.00009095109,0.0001943937,0.0003584889,0.0001617953,0.0001398402],"domain_scores_gemma":[0.9997036,0.00002912336,0.00007688504,0.00008683647,0.0000312523,0.00007229218],"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":[0.0007981764,0.0007069585,0.04685141,0.0023323,0.0000520574,0.0001122823,0.007455487,0.8680878,0.01226252,0.004117658,0.01176082,0.04546251],"study_design_scores_gemma":[0.0007880825,0.0002367796,0.002376336,0.0001021612,0.00002241854,0.00001920388,0.0001646743,0.9951791,0.0004917092,0.00004144343,0.0004209669,0.0001571215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01477897,0.00009367546,0.979921,0.00392077,0.0005046847,0.0004807972,0.00001893197,0.0001425863,0.0001385928],"genre_scores_gemma":[0.9228995,0.0001585828,0.07539924,0.001399196,0.00007206246,0.000009395666,0.0000201093,0.00001808639,0.00002377884],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9081206,"threshold_uncertainty_score":0.4471194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01860647781684425,"score_gpt":0.2468521562389543,"score_spread":0.2282456784221101,"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."}}