{"id":"W4404245067","doi":"10.7554/elife.95764.4","title":"Shortcutting from self-motion signals reveals a cognitive map in mice","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Krembil Foundation","keywords":"Spatial learning; Cognitive map; Hippocampal formation; Motion (physics); Artificial intelligence; Cognition; Computer science; Spatial cognition; Dynamics (music); Computer vision; Hippocampus; Pattern recognition (psychology); Machine learning; Biology; Neuroscience; Psychology","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":[0.0002193492,0.0004167848,0.0003373728,0.0003497757,0.0001174747,0.0004686567,0.0006050342,0.0005488116,0.0007534501],"category_scores_gemma":[0.0007201117,0.0003335782,0.0003623492,0.0001215401,0.000582441,0.0004511648,0.0005515206,0.001160584,0.0001642338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002555621,"about_ca_system_score_gemma":0.0002291311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006386967,"about_ca_topic_score_gemma":0.0008829272,"domain_scores_codex":[0.9998749,0.000009832842,0.000007230301,0.00003777126,0.00004183446,0.0000283159],"domain_scores_gemma":[0.9994947,0.00008189033,0.0001941799,0.00008398914,0.00004319352,0.0001019336],"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":[0.0001907028,0.00003318184,0.001797632,0.00003697045,0.00002928494,0.0001516612,0.00006891626,0.003424896,0.9830041,0.001348496,0.0001085222,0.009805677],"study_design_scores_gemma":[0.00008829233,0.001450119,0.0661064,0.00003990714,0.00008181537,0.0007463704,0.000160285,0.09030367,0.8302054,0.008003682,0.00274733,0.0000667529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9656759,0.0001228444,0.03304044,0.00008664478,0.00001677805,0.000007548559,0.0001655069,0.0003251732,0.0005591389],"genre_scores_gemma":[0.9762165,0.0001551541,0.02138539,0.00007735686,0.000009668514,0.0000315507,0.0003078471,0.0001488487,0.001667604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007534501,"threshold_uncertainty_score":0.002520561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0779091579498919,"score_gpt":0.3295994424888262,"score_spread":0.2516902845389343,"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."}}