{"id":"W2576223904","doi":"10.5594/m001703","title":"Is There an Uncanny Valley in Frame Rate Perception?","year":2016,"lang":"en","type":"article","venue":"","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Zymeworks (Canada)","funders":"","keywords":"Perception; Artificial intelligence; Computer vision; Computer science; Frame rate; Uncanny valley; Frame (networking); Percept; Uncanny; Motion (physics); Computer graphics (images); Robot; Aesthetics; Psychology; Art","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002495171,0.0002866135,0.0007053699,0.001309851,0.0006447484,0.003829152,0.0009363854,0.001058832,0.003538493],"category_scores_gemma":[0.02329327,0.0006817676,0.0005604484,0.0006423313,0.00375365,0.007959939,0.001555852,0.002308754,0.0005686063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007646522,"about_ca_system_score_gemma":0.0005512481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001197853,"about_ca_topic_score_gemma":0.0008164677,"domain_scores_codex":[0.9988519,0.0001970657,0.00006593436,0.0003450797,0.0004574319,0.00008254674],"domain_scores_gemma":[0.9931285,0.002979098,0.001365421,0.001248459,0.0009386861,0.0003397627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009280544,0.0002605662,0.05414869,0.0008743056,0.0002756851,0.0004412521,0.008884217,0.005780855,0.1190613,0.2967106,0.006041013,0.5065936],"study_design_scores_gemma":[0.0001032221,0.001009752,0.359947,0.0005682376,0.0001085762,0.0021159,0.005368895,0.04022216,0.02487992,0.5456406,0.01969409,0.0003415214],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5906577,0.006704476,0.3330851,0.01596639,0.0003610848,0.0001703302,0.0006844972,0.001161814,0.05120865],"genre_scores_gemma":[0.9504976,0.001133384,0.04561794,0.000681644,0.0001926731,0.00006882574,0.0001450721,0.0002739403,0.001388927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003829152,"threshold_uncertainty_score":0.01319587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08313896487880619,"score_gpt":0.352235831844751,"score_spread":0.2690968669659448,"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."}}