{"id":"W2031776850","doi":"10.1016/j.visres.2007.08.003","title":"Object perception and masking: Contributions of sides and convexities","year":2007,"lang":"en","type":"article","venue":"Vision Research","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Masking (illustration); Perception; Convexity; Backward masking; Coding (social sciences); Object (grammar); Computer science; Psychology; Communication; Physics; Mathematics; Artificial intelligence; Statistics; Neuroscience; Art","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002040928,0.00006340287,0.0001025481,0.0002793494,0.0003786622,0.00008953067,0.00007715615,0.00007389334,0.0002374164],"category_scores_gemma":[0.001036603,0.00005355299,0.00001653465,0.0003127257,0.000518533,0.0001398532,0.0001027366,0.0002115484,0.00002568458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002152365,"about_ca_system_score_gemma":0.0000353352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003322471,"about_ca_topic_score_gemma":0.000006822303,"domain_scores_codex":[0.9986705,0.0002005101,0.0001658573,0.000242927,0.0004638683,0.0002564057],"domain_scores_gemma":[0.9989727,0.0006068199,0.00003193307,0.0001022992,0.0001775701,0.0001087355],"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":[0.00005697084,0.0000317675,0.0002013346,0.00003987094,5.889877e-7,0.000003254068,0.0008373749,3.246336e-7,0.9757433,0.006361188,0.0001654914,0.01655854],"study_design_scores_gemma":[0.0007746114,0.000906897,0.03874358,0.0001381668,0.00000402112,0.00004835727,0.005456343,0.001777839,0.9331782,0.01558025,0.003227982,0.0001637743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929741,0.00007538485,0.003362352,0.0004112101,0.00004835664,0.000154654,0.00001112891,0.00003334789,0.00292946],"genre_scores_gemma":[0.998669,0.000275399,0.0001971436,0.0001165522,0.00003175412,0.000003103868,0.000001411595,0.000007016528,0.0006986494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04256511,"threshold_uncertainty_score":0.2912402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1398413062324081,"score_gpt":0.476230272576371,"score_spread":0.3363889663439629,"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."}}