{"id":"W2117875009","doi":"10.1016/s0010-0277(02)00075-6","title":"Mental image generation and the contrast sensitivity function","year":2002,"lang":"en","type":"article","venue":"Cognition","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Contrast (vision); Mental image; Psychology; Functional magnetic resonance imaging; Perception; Visual perception; Computer vision; Artificial intelligence; Sensitivity (control systems); Image contrast; Communication; Cognitive psychology; Cognition; Neuroscience; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001747514,0.00005452578,0.00004782275,0.00002017107,0.0003200397,0.000106281,0.00001349478,0.00002674817,0.000351341],"category_scores_gemma":[0.0001171206,0.0000397494,0.00001718121,0.00006089049,0.0001190389,0.000224939,0.000009787589,0.00006046279,0.0001924577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007522874,"about_ca_system_score_gemma":0.000001689354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.950168e-7,"about_ca_topic_score_gemma":0.000003701995,"domain_scores_codex":[0.9994295,0.0001782198,0.00006810934,0.000145799,0.0001060686,0.0000722549],"domain_scores_gemma":[0.9998239,0.00005122855,0.00003367635,0.00004185875,0.00002548229,0.00002383221],"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":[0.00003318585,0.00002112691,0.000001078207,0.000002744595,7.099575e-7,0.000001024364,0.0002866475,3.206453e-7,0.9735541,0.0005897988,0.0005861512,0.02492313],"study_design_scores_gemma":[0.00252751,0.00009448756,0.0003783363,0.00001353309,0.00003700479,0.0001095974,0.0001740325,0.1892606,0.8035915,0.003014192,0.0006536291,0.000145589],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9414278,0.00003930893,0.04609555,0.001972552,0.0005291176,0.000336541,0.00001882356,0.0001288331,0.009451455],"genre_scores_gemma":[0.9969042,0.0000659665,0.00003559466,0.002577414,0.0001469023,0.00001035453,0.00001075525,0.00000509862,0.0002437436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1892603,"threshold_uncertainty_score":0.3846937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07535595793453366,"score_gpt":0.2810701620137127,"score_spread":0.2057142040791791,"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."}}