{"id":"W3029249725","doi":"10.1038/s41467-020-15805-9","title":"Sources of path integration error in young and aging humans","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research; Bundesministerium für Bildung und Forschung; Simons Foundation; Howard Hughes Medical Institute; National Science Foundation","keywords":"Path integration; Path (computing); Noise (video); Integrator; Computer science; Numerical integration; Mathematics; Artificial intelligence; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001000143,0.0004019027,0.0004180396,0.0009695968,0.0001737176,0.0006065547,0.0002381547,0.0004700717,0.0008232559],"category_scores_gemma":[0.008934678,0.0002341849,0.0001582597,0.000420586,0.0004919504,0.0006841088,0.0007333583,0.0002728811,0.0001535852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000176283,"about_ca_system_score_gemma":0.000236642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002603118,"about_ca_topic_score_gemma":0.00214704,"domain_scores_codex":[0.9996845,0.0000437239,0.00002974332,0.0001081519,0.0001118876,0.00002197875],"domain_scores_gemma":[0.9970343,0.001231075,0.0008811647,0.0002939223,0.0004035309,0.0001560084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002302293,0.0002229894,0.681976,0.0003428512,0.0004560922,0.001520093,0.007906956,0.01033727,0.09713718,0.003239013,0.001173724,0.1933856],"study_design_scores_gemma":[0.00001558906,0.0002632378,0.9777449,0.00003823076,0.00009431672,0.001246187,0.0005173028,0.00954417,0.004416541,0.005376327,0.0006723258,0.00007098302],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939353,0.0005440848,0.004772185,0.00004443262,0.000009315529,0.000007795221,0.0001737334,0.00003523004,0.0004778889],"genre_scores_gemma":[0.9967776,0.0001619601,0.00246329,0.00002491081,0.00001045843,0.00001119881,0.0001627664,0.00002945249,0.0003583482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002603118,"threshold_uncertainty_score":0.005289316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02410869112178025,"score_gpt":0.2808770098962246,"score_spread":0.2567683187744443,"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."}}