{"id":"W1971200370","doi":"10.1371/journal.pcbi.1002196","title":"A Single-Rate Context-Dependent Learning Process Underlies Rapid Adaptation to Familiar Object Dynamics","year":2011,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Context (archaeology); Adaptation (eye); Computer science; Artificial intelligence; Process (computing); Object (grammar); Dynamics (music); Generalization; Psychology; Mathematics; Neuroscience; Biology","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":[0.0003939316,0.0003690369,0.0006052341,0.000212957,0.000183109,0.0004134326,0.0004469201,0.000389315,0.001109216],"category_scores_gemma":[0.001978179,0.0002726023,0.0006230435,0.0001500399,0.0005197406,0.0006686832,0.0006072833,0.0007135005,0.0002416474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003445655,"about_ca_system_score_gemma":0.0003466749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001225336,"about_ca_topic_score_gemma":0.001059519,"domain_scores_codex":[0.9998166,0.00002192394,0.00001369634,0.00007685871,0.00004016663,0.00003076336],"domain_scores_gemma":[0.9992365,0.0002472975,0.0002061813,0.0001575316,0.00008205247,0.00007042893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004316095,0.0003397615,0.01759883,0.0002792821,0.0001940454,0.0005373331,0.0003403642,0.1104109,0.7656148,0.01332845,0.0003954849,0.09052926],"study_design_scores_gemma":[0.00002485281,0.000342433,0.04833432,0.00001696034,0.00006851227,0.0005093398,0.00003730373,0.8890975,0.0482813,0.01250668,0.00071119,0.00006966589],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8602933,0.000384237,0.1367513,0.0001220042,0.00004190024,0.00005978595,0.00008346672,0.0004398729,0.001824138],"genre_scores_gemma":[0.9940119,0.0001306052,0.005229329,0.00001493966,0.000007576909,0.0000218716,0.00003691756,0.00002445105,0.0005223136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001225336,"threshold_uncertainty_score":0.003710687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08539139755442322,"score_gpt":0.2613603982830945,"score_spread":0.1759690007286713,"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."}}