{"id":"W2103120111","doi":"10.1037/a0029877","title":"The role of clarity and blur in guiding visual attention in photographs.","year":2012,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Department of Psychology, Western Washington University","keywords":"CLARITY; Eye tracking; Gaze; Psychology; Cognitive psychology; Computer vision; Artificial intelligence; Computer science","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":[0.001090992,0.0002444066,0.0001776999,0.000709062,0.0003190323,0.0007484305,0.0002758724,0.0003740754,0.0007827362],"category_scores_gemma":[0.01108772,0.0002694375,0.000234168,0.0002080612,0.0003853489,0.001270609,0.0006110272,0.0002711559,0.0001198735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004596767,"about_ca_system_score_gemma":0.0002713281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002173268,"about_ca_topic_score_gemma":0.002091843,"domain_scores_codex":[0.9995517,0.0001654378,0.00002489272,0.00007261337,0.0001336721,0.00005162148],"domain_scores_gemma":[0.9969832,0.001601281,0.0006908538,0.0001844688,0.0003313435,0.0002088213],"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":[0.002755704,0.0001445219,0.1017981,0.0005583718,0.0001505869,0.0003772492,0.00594501,0.002148646,0.7029881,0.004915268,0.0009354674,0.177283],"study_design_scores_gemma":[0.00007767472,0.0012149,0.9157734,0.0001067527,0.0001603139,0.0008510065,0.001799479,0.01522296,0.05573511,0.006513109,0.002462981,0.00008237846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692769,0.001927924,0.02351752,0.0001639416,0.000035047,0.00006451739,0.00003170657,0.00006930538,0.004913138],"genre_scores_gemma":[0.9956853,0.0002187784,0.003805753,0.00003161248,0.000009519944,0.00001011455,0.00001439848,0.0000095869,0.0002148814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002173268,"threshold_uncertainty_score":0.005769789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011454207001615,"score_gpt":0.3601237212665341,"score_spread":0.330009179196518,"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."}}