{"id":"W7001229301","doi":"","title":"Implicit and Explicit Adaptation Just Don’t Add Up","year":2023,"lang":"en","type":"article","venue":"","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; York University","funders":"","keywords":"Adaptation (eye); Implicit-association test; Set (abstract data type); Neural adaptation; Additive function; Implicit knowledge","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":[0.007124002,0.0009426438,0.001569053,0.0009940459,0.0006677664,0.002466086,0.001406304,0.001063608,0.007535485],"category_scores_gemma":[0.03861948,0.0009100981,0.001125505,0.000806106,0.003643729,0.004618196,0.004308092,0.003569025,0.002279191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006442143,"about_ca_system_score_gemma":0.0008609314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303228,"about_ca_topic_score_gemma":0.001536434,"domain_scores_codex":[0.9875895,0.00219361,0.00161731,0.00362694,0.004217548,0.0007551352],"domain_scores_gemma":[0.9672701,0.01281061,0.003260179,0.01316775,0.00252686,0.0009645263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003106746,0.001036057,0.2557365,0.002953634,0.003538272,0.0006793569,0.004552301,0.002938366,0.1322733,0.03167306,0.004703473,0.5568089],"study_design_scores_gemma":[0.0001462138,0.001641771,0.8506483,0.0006159401,0.001220378,0.002465723,0.001364618,0.008130434,0.05574716,0.06076315,0.0169258,0.0003305219],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7901909,0.004586441,0.1348045,0.003367584,0.001386142,0.000649974,0.001136102,0.001527561,0.06235076],"genre_scores_gemma":[0.9746207,0.0005385525,0.01624589,0.001788588,0.0001725489,0.0003321502,0.0006630931,0.0004396419,0.005198854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007535485,"threshold_uncertainty_score":0.0376758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08196791188793993,"score_gpt":0.2884148097677527,"score_spread":0.2064468978798127,"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."}}