{"id":"W2898236089","doi":"10.1037/xlm0000660","title":"Examining the hierarchical nature of scene representations in memory.","year":2018,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Scene statistics; Representation (politics); Set (abstract data type); Block (permutation group theory); Hierarchy; Hierarchical database model; Computer vision; Natural language processing; Psychology; Mathematics; Database; Perception","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":[0.0006226763,0.0002297762,0.0002010312,0.0007296591,0.0002843281,0.001352673,0.0007856318,0.0005861293,0.00373665],"category_scores_gemma":[0.0055646,0.0001880189,0.0001957648,0.0005784136,0.001025674,0.005366537,0.0007823726,0.0007400214,0.0003569625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00077208,"about_ca_system_score_gemma":0.0005708184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002966973,"about_ca_topic_score_gemma":0.004346976,"domain_scores_codex":[0.9998322,0.00003106961,0.00001032962,0.00006293083,0.00004162803,0.00002187088],"domain_scores_gemma":[0.9982318,0.0008335325,0.0004491843,0.0002415137,0.0001309985,0.0001129504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001701549,0.0007292596,0.06905145,0.001686297,0.0002304925,0.0005601958,0.005561068,0.005502352,0.2917272,0.03742091,0.004332089,0.5814973],"study_design_scores_gemma":[0.0003326547,0.004472277,0.5146073,0.0005983572,0.0005991285,0.001515284,0.00649096,0.06439895,0.1367598,0.2564599,0.01358922,0.0001760855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627085,0.002474261,0.02221428,0.001018984,0.00005447603,0.00008565984,0.0001973557,0.0001146771,0.0111318],"genre_scores_gemma":[0.9894621,0.0008213671,0.007682904,0.0001604088,0.00001810577,0.00004430949,0.0002245326,0.00001364989,0.001572726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00373665,"threshold_uncertainty_score":0.01250035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03986606591747405,"score_gpt":0.3739641139099199,"score_spread":0.3340980479924459,"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."}}