{"id":"W1935169546","doi":"10.1037/xhp0000106","title":"Endogenous strategy in exploration.","year":2015,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Correlation; Autocorrelation; Sampling (signal processing); Value (mathematics); Mathematics; Computer science; Task (project management); Spatial analysis; Artificial intelligence; Visual search; Pattern recognition (psychology); Statistics; Computer vision; Engineering; 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":[0.0008251235,0.0002315369,0.0002308472,0.0004464922,0.0002104398,0.0009274667,0.000329213,0.0004224706,0.001370145],"category_scores_gemma":[0.007001863,0.0001545444,0.0002496966,0.0003642435,0.00062403,0.0008618208,0.0009828162,0.0003475083,0.0001535776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003821788,"about_ca_system_score_gemma":0.0003509381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008266144,"about_ca_topic_score_gemma":0.0009699926,"domain_scores_codex":[0.9993113,0.0002078245,0.00003737976,0.0001923319,0.000185761,0.00006538122],"domain_scores_gemma":[0.9978861,0.0008371671,0.0005260518,0.000428215,0.0001496092,0.0001727998],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001280274,0.0003559181,0.1687045,0.0008770686,0.0004310501,0.0007816877,0.007018312,0.02155778,0.3876718,0.1148578,0.001726352,0.2947375],"study_design_scores_gemma":[0.0001698671,0.001812819,0.6563404,0.0001556656,0.0002448429,0.002674261,0.00207003,0.1715337,0.03724082,0.1157337,0.01184728,0.0001765792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9540698,0.0004569929,0.03647785,0.0001151517,0.00001310582,0.00004552556,0.00007482467,0.0001176429,0.008629257],"genre_scores_gemma":[0.9908094,0.00005978362,0.008304082,0.00002838543,0.000004207878,0.00003548744,0.00004433193,0.00001867939,0.0006955681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001370145,"threshold_uncertainty_score":0.004583538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.185296723672028,"score_gpt":0.3978520225880809,"score_spread":0.2125552989160528,"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."}}