{"id":"W2049687820","doi":"10.1016/s0926-6410(00)00002-1","title":"The effects of sequence structure and reward schedule on serial reaction time learning in the monkey","year":2000,"lang":"en","type":"article","venue":"Cognitive Brain Research","topic":"Child and Animal Learning Development","field":"Psychology","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Serial reaction time; Sequence learning; Sequence (biology); Psychology; Schedule; Context (archaeology); Implicit learning; Serial learning; Communication; Cognition; Artificial intelligence; Cognitive psychology; Neuroscience; Computer science; Biology","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":[0.0003029223,0.0003403862,0.0003298026,0.000282626,0.0002205544,0.0004457019,0.0003901424,0.0004150814,0.001355791],"category_scores_gemma":[0.003239108,0.0003231267,0.0001677329,0.0001584027,0.0006461411,0.0003387207,0.000258242,0.0007823827,0.0002178381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003720828,"about_ca_system_score_gemma":0.0004624903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002879749,"about_ca_topic_score_gemma":0.003015626,"domain_scores_codex":[0.9998562,0.00004703469,0.00001016776,0.0000313867,0.0000308927,0.00002432601],"domain_scores_gemma":[0.997839,0.001221987,0.0003432154,0.0001949709,0.00008545262,0.000315443],"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":[0.006851094,0.0005804593,0.009566631,0.00008631445,0.0000843424,0.0002425495,0.0002427282,0.003371556,0.940661,0.001241157,0.000235921,0.0368362],"study_design_scores_gemma":[0.001040596,0.01640157,0.3883898,0.0000665799,0.000464786,0.001502087,0.0003915956,0.07175089,0.4997589,0.01715746,0.002912814,0.000162835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989045,0.00006768367,0.0003990925,0.00004754921,0.000004997738,0.00000234567,0.00002188993,0.00001749745,0.0005345021],"genre_scores_gemma":[0.9977697,0.0002357871,0.0008907779,0.00005127953,0.00001388082,0.00001192051,0.00008798469,0.00007875247,0.0008598654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002879749,"threshold_uncertainty_score":0.00572598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03613882299968123,"score_gpt":0.3780331046705253,"score_spread":0.341894281670844,"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."}}