{"id":"W3175348627","doi":"10.31234/osf.io/rkh8g","title":"Salience by Competitive and Recurrent Interactions: Bridging Neural Spiking and Computation in Visual Attention","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Eye Institute; Australian Research Council","keywords":"Salience (neuroscience); Saccade; Stimulus (psychology); Computer science; Neuroscience; Eye movement; Computational model; Saccadic masking; Psychology; Artificial intelligence; Cognitive psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004009072,0.000319018,0.0003405295,0.0002475228,0.0002830871,0.0009739993,0.0008574724,0.0006616701,0.0007876453],"category_scores_gemma":[0.001654576,0.0003783483,0.0006055598,0.0002351892,0.0008830077,0.001397249,0.0008251597,0.0006135391,0.0001353086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009915971,"about_ca_system_score_gemma":0.000368077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003033168,"about_ca_topic_score_gemma":0.002432904,"domain_scores_codex":[0.9998137,0.0000499846,0.000008971501,0.00005101996,0.00004322384,0.00003307181],"domain_scores_gemma":[0.9995883,0.0001968851,0.00007361776,0.00006117391,0.00003550923,0.00004451605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004133754,0.0001374257,0.007306216,0.0001213187,0.0002098823,0.0004177668,0.0008106092,0.6067936,0.1665379,0.1465451,0.0009768796,0.06973],"study_design_scores_gemma":[0.00001086021,0.00004002762,0.001483067,0.000003913177,0.00001350257,0.00004557829,0.00002110653,0.9545293,0.003630737,0.03994624,0.0002596018,0.00001606797],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5344265,0.0006695514,0.456624,0.0008403399,0.00004725409,0.00003208845,0.00007676989,0.0004126835,0.006870818],"genre_scores_gemma":[0.9829431,0.0001265469,0.01633157,0.00004317537,0.00001458953,0.00001753513,0.00001998738,0.00002485468,0.0004786901],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003033168,"threshold_uncertainty_score":0.007194579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06315812081925641,"score_gpt":0.3806696232491246,"score_spread":0.3175115024298681,"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."}}