{"id":"W4396770408","doi":"10.7554/elife.95764.1","title":"Shortcutting from self-motion signals: quantifying trajectories and active sensing in an open maze","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Krembil Foundation","keywords":"Motion (physics); Computer science; Artificial intelligence","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":[0.0002165265,0.0002754907,0.0001805279,0.0003378834,0.00009472593,0.0002802743,0.0003197314,0.0002553047,0.000436313],"category_scores_gemma":[0.001367871,0.000137568,0.0001290658,0.0001673389,0.000417799,0.0004722425,0.0003965064,0.0002947176,0.00006293983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002126074,"about_ca_system_score_gemma":0.0001315285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009199301,"about_ca_topic_score_gemma":0.0009231194,"domain_scores_codex":[0.9999447,0.00001072413,0.000002355172,0.00001444873,0.00001940762,0.000008323431],"domain_scores_gemma":[0.9996296,0.0001355711,0.0001139269,0.00003238152,0.00003925019,0.00004926567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004997328,0.0001330335,0.02308704,0.0001372566,0.00009934285,0.0003144972,0.0003338213,0.2407629,0.6604113,0.01069865,0.0003354011,0.06318706],"study_design_scores_gemma":[0.000009156064,0.0001717893,0.02471547,0.00001041728,0.000009588446,0.0001077804,0.00005294387,0.9256475,0.04200277,0.006969158,0.0002777921,0.0000256844],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8946272,0.00005982301,0.1047099,0.00003088883,0.000005234275,0.000008485337,0.00008462746,0.0001156301,0.0003582408],"genre_scores_gemma":[0.9871709,0.00003257117,0.01248058,0.00000453969,0.000001797909,0.00000710319,0.00005022634,0.00001638942,0.000235891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009199301,"threshold_uncertainty_score":0.001829147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1091394221300773,"score_gpt":0.3480252363938018,"score_spread":0.2388858142637245,"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."}}