{"id":"W7014951413","doi":"","title":"Recognising faces and reading words : investigations into visual perceptual expertise","year":2020,"lang":"en","type":"dissertation","venue":"Warwick Research Archive Portal (University of Warwick)","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Perception; Frame (networking); Nasalization; Noise (video); Feature (linguistics); Subject (documents)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004019983,0.0002563596,0.0001629951,0.0005715907,0.0001820152,0.0003743526,0.000202423,0.0005699845,0.002881752],"category_scores_gemma":[0.002069899,0.0001643872,0.0001330601,0.0001980083,0.0007563247,0.0008223883,0.0004223243,0.0004666474,0.0002925051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001625111,"about_ca_system_score_gemma":0.00009287702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009646753,"about_ca_topic_score_gemma":0.0007314982,"domain_scores_codex":[0.9997719,0.00005330763,0.00001317286,0.00006725663,0.00006212651,0.0000322795],"domain_scores_gemma":[0.9986542,0.0006979562,0.0002466568,0.0001086058,0.0001378433,0.0001545961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001788807,0.001918281,0.1075786,0.000400769,0.00006918459,0.001313198,0.01394032,0.0005267705,0.723177,0.001631713,0.0005327795,0.1471225],"study_design_scores_gemma":[0.00004037327,0.00360712,0.9322247,0.00003395765,0.00003923425,0.002182223,0.003823602,0.001685676,0.0521431,0.002420364,0.001755376,0.0000442243],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966803,0.0001811066,0.0007078876,0.0000627999,0.000004004133,0.00001582639,0.00002388849,0.000005422575,0.002318706],"genre_scores_gemma":[0.9975137,0.0001884089,0.00107512,0.00005696151,0.00001347446,0.0000160411,0.00003176179,0.000004315931,0.001100311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002881752,"threshold_uncertainty_score":0.009640455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08905720014574052,"score_gpt":0.3452643200085626,"score_spread":0.2562071198628221,"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."}}