{"id":"W3133085333","doi":"10.1101/2021.02.17.431605","title":"Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University Health Centre","keywords":"Jitter; Perception; Texture (cosmology); Wavelet; Mathematics; Artificial intelligence; Orientation (vector space); Pattern recognition (psychology); Visual perception; Computer vision; Communication; Computer science; Psychology; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003535045,0.000386162,0.0005511584,0.00114421,0.0001870379,0.001055568,0.00078843,0.0006975214,0.001391547],"category_scores_gemma":[0.0130186,0.0003944058,0.0009840942,0.0007697733,0.000772909,0.0009776363,0.0007249,0.0006939423,0.0001816947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007036643,"about_ca_system_score_gemma":0.0002432892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001879584,"about_ca_topic_score_gemma":0.0006358114,"domain_scores_codex":[0.9990116,0.0004777266,0.00003820838,0.0001799377,0.0002116229,0.00008080849],"domain_scores_gemma":[0.9946401,0.003588091,0.0005674894,0.0006294206,0.000373548,0.0002015107],"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":[0.002930298,0.0005947606,0.0844463,0.0005505257,0.0006737898,0.0007931885,0.001197047,0.526243,0.2220076,0.03873145,0.001080016,0.120752],"study_design_scores_gemma":[0.00001678713,0.00007387272,0.01748752,0.000007249707,0.00002218036,0.00008715606,0.00002550807,0.970637,0.002679144,0.008863488,0.00006654898,0.00003354709],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6238415,0.0001749526,0.3740183,0.000162994,0.00002124312,0.00009282249,0.0001576809,0.0002427096,0.001287721],"genre_scores_gemma":[0.986073,0.00003310088,0.01365121,0.00001943864,0.000004825554,0.00001724962,0.00002843022,0.00001547019,0.0001572496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003535045,"threshold_uncertainty_score":0.01869535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0554127813874457,"score_gpt":0.285174431083802,"score_spread":0.2297616496963563,"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."}}