{"id":"W4411770162","doi":"10.1101/2025.06.26.661747","title":"REACTIVATION PROTECTS MOTOR MEMORIES FROM INTERFERENCE BY COMPETING LEARNING","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Department of Science and Technology, Ministry of Science and Technology, India; Indian Institute of Technology Gandhinagar","keywords":"Interference (communication); Computer science; Psychology; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003828472,0.0004050344,0.0004821592,0.0001616819,0.0001295604,0.0004534532,0.0007940124,0.0003130611,0.002898962],"category_scores_gemma":[0.001172248,0.0001855825,0.0002859707,0.0001044133,0.0007141267,0.0005645512,0.0007893649,0.00101987,0.0004049991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002752033,"about_ca_system_score_gemma":0.0002507324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004397805,"about_ca_topic_score_gemma":0.0004856081,"domain_scores_codex":[0.9997391,0.00003858861,0.00003518146,0.00006434425,0.0000537214,0.0000690807],"domain_scores_gemma":[0.9994059,0.0001667851,0.0001276695,0.0001934961,0.00004738522,0.00005870364],"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":[0.0005820424,0.0001075525,0.0005366092,0.00007271836,0.0000272871,0.00007168648,0.0000567447,0.0005163245,0.9894859,0.0004121713,0.00005782158,0.00807336],"study_design_scores_gemma":[0.00005021737,0.001022955,0.005596391,0.0000209152,0.00004119972,0.0001612585,0.00004741454,0.003983073,0.9876293,0.0007091216,0.0007215269,0.00001659946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924913,0.0005715486,0.005507074,0.00004891205,0.00004420639,0.00002269224,0.00006091494,0.0001055287,0.001147805],"genre_scores_gemma":[0.9976947,0.0001414373,0.001098115,0.00004167355,0.00000929109,0.00002007624,0.00005888851,0.0000415529,0.0008943271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002898962,"threshold_uncertainty_score":0.009697974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01935241928953853,"score_gpt":0.2342304728367614,"score_spread":0.2148780535472228,"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."}}