{"id":"W3081632823","doi":"10.3390/brainsci10090598","title":"A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations","year":2020,"lang":"en","type":"article","venue":"Brain Sciences","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"University of Toronto","keywords":"Unobservable; Series (stratigraphy); SIGNAL (programming language); Computer science; Trajectory; Time series; Perspective (graphical); Econometrics; Mathematics; Artificial intelligence; Machine learning; 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":[0.002834603,0.000491347,0.0003735228,0.0007292586,0.000128349,0.0007365156,0.000589903,0.0004646285,0.001082889],"category_scores_gemma":[0.0249513,0.0001850739,0.0005252791,0.0007460805,0.0003069619,0.001390841,0.0004699382,0.0008285117,0.0002193979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002282861,"about_ca_system_score_gemma":0.0003621268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002237701,"about_ca_topic_score_gemma":0.001206387,"domain_scores_codex":[0.9989992,0.0004044384,0.00006816506,0.0002734887,0.0002211699,0.00003365442],"domain_scores_gemma":[0.9909774,0.006613884,0.0008052812,0.0007489668,0.0007554233,0.00009896946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001437426,0.0004512145,0.1524003,0.0005834641,0.00124332,0.0003097587,0.001483254,0.2987338,0.0498019,0.02503723,0.001490687,0.4670276],"study_design_scores_gemma":[0.00002806624,0.0004044999,0.1323642,0.00005654051,0.0001807208,0.0002197224,0.0001556164,0.8453284,0.01070162,0.008724289,0.001729604,0.0001067491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5138087,0.0005938482,0.4821526,0.0001921864,0.00007671145,0.00005311256,0.0002701848,0.0002999565,0.002552796],"genre_scores_gemma":[0.9536262,0.0001963791,0.04496609,0.00002563826,0.00003060391,0.00003750979,0.0004598042,0.00005716899,0.0006005686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002834603,"threshold_uncertainty_score":0.01499099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04390726982965544,"score_gpt":0.3037346303293147,"score_spread":0.2598273604996593,"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."}}