{"id":"W4383223592","doi":"10.3389/fnins.2023.1190515","title":"Exploiting semantic information in a spiking neural SLAM system","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Artificial intelligence; Simultaneous localization and mapping; Computer vision; Cognitive map; Pattern recognition (psychology); Robot; Mobile robot; Cognition","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002314384,0.0001080197,0.0001364309,0.0004378508,0.00007674746,0.00005067465,0.0002103615,0.00002895233,1.85681e-7],"category_scores_gemma":[0.0001130735,0.0001189312,0.00002158141,0.001468964,0.00002970136,0.001021837,0.00006214673,0.0002164013,0.000007675863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008363912,"about_ca_system_score_gemma":0.000006628489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002428856,"about_ca_topic_score_gemma":0.000001502955,"domain_scores_codex":[0.9989812,0.00002502286,0.0002780974,0.0001628452,0.0001603298,0.0003925008],"domain_scores_gemma":[0.9997681,0.00003000036,0.00003588395,0.0001203681,0.000007544279,0.00003815351],"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":[0.000004398696,0.000002198228,0.009965518,0.0001775586,2.507882e-7,0.00008983826,0.0006334946,0.9675698,0.01023757,0.00006655059,0.0001107025,0.0111421],"study_design_scores_gemma":[0.0001458658,0.000013317,0.01149523,0.0001226691,6.420499e-7,0.000014175,0.0007669433,0.9851802,0.001907205,0.00004022736,0.0001910635,0.0001224517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622826,0.0000273306,0.03343198,0.00002055615,0.003101271,0.0001476871,9.2654e-7,0.0005809235,0.0004067417],"genre_scores_gemma":[0.9993431,0.0000149082,0.0005190702,0.00006004722,0.0000296794,0.00001249837,0.000001200471,0.00001077707,0.000008715448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03706052,"threshold_uncertainty_score":0.4849874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01474928068527864,"score_gpt":0.2180863382878423,"score_spread":0.2033370576025636,"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."}}