{"id":"W2973903212","doi":"10.1167/19.10.58d","title":"Generating visual stimuli that vary in recognisability","year":2019,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Limiting; Computer science; Class (philosophy); Visual processing; Visual perception; Artificial intelligence; Pattern recognition (psychology); Perception; Psychology; Neuroscience","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":[0.0006133941,0.000463128,0.0003337077,0.0003568289,0.0001955087,0.0009917615,0.0006502619,0.0006828015,0.003885551],"category_scores_gemma":[0.005329131,0.0003296554,0.00038034,0.0002456853,0.0005433513,0.001244444,0.000845593,0.0008103579,0.0006423597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000355433,"about_ca_system_score_gemma":0.000166627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001357971,"about_ca_topic_score_gemma":0.0001649105,"domain_scores_codex":[0.999711,0.00004842009,0.00002999353,0.00007942072,0.00009485566,0.00003624917],"domain_scores_gemma":[0.9980071,0.001046932,0.0002166511,0.0004394909,0.0001868339,0.000103058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004087368,0.000177698,0.000986672,0.0002914805,0.00003669889,0.000208589,0.0001374415,0.007973787,0.942427,0.006880724,0.0004683379,0.04000276],"study_design_scores_gemma":[0.0001875695,0.001810234,0.01014302,0.0000942265,0.0001299537,0.001275168,0.0002054155,0.08339782,0.8775827,0.01432243,0.01072417,0.0001272369],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7859014,0.000511652,0.199167,0.0003115936,0.0002949324,0.0004558367,0.0003605658,0.001230489,0.01176655],"genre_scores_gemma":[0.8780941,0.0003593287,0.1171732,0.0003388695,0.00003081562,0.0003288439,0.0004073862,0.0004464646,0.002820961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003885551,"threshold_uncertainty_score":0.0129984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08709259513539361,"score_gpt":0.3931849877424322,"score_spread":0.3060923926070386,"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."}}