{"id":"W2504716999","doi":"10.1371/journal.pone.0158466","title":"Noise Induces Biased Estimation of the Correction Gain","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Science Foundation","keywords":"Noise (video); Computer science; Identification (biology); Fraction (chemistry); Set (abstract data type); Statistics; Regression; Algorithm; Mathematics; Artificial intelligence","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":[0.00308622,0.0006931561,0.001119637,0.0007305208,0.0003366381,0.0009217414,0.0009001053,0.00111053,0.0006763396],"category_scores_gemma":[0.03110415,0.0005641037,0.0004747438,0.0004527442,0.0009673536,0.001454597,0.001105805,0.001271227,0.0004288896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006524175,"about_ca_system_score_gemma":0.0008922848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001907997,"about_ca_topic_score_gemma":0.001455251,"domain_scores_codex":[0.9971811,0.0006993994,0.0002247692,0.0008454086,0.0008714308,0.0001779424],"domain_scores_gemma":[0.9880167,0.008409228,0.001085338,0.001154262,0.001242644,0.00009185118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001157774,0.0002982976,0.03377153,0.00085101,0.0003670869,0.0009963956,0.001466088,0.269246,0.3028483,0.03768533,0.001857218,0.3494549],"study_design_scores_gemma":[0.00002646759,0.0001468855,0.01775227,0.00008019617,0.00005643539,0.0007293618,0.00006546969,0.8732987,0.08768627,0.01839859,0.001628786,0.0001306463],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1201208,0.0003220935,0.8771051,0.0002584907,0.00009936152,0.00004274341,0.00007157588,0.0005742589,0.001405511],"genre_scores_gemma":[0.8803293,0.0002831074,0.1173994,0.0001890281,0.00003791871,0.00008192644,0.0001821463,0.0002092412,0.001288059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00308622,"threshold_uncertainty_score":0.01632172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07531155706373331,"score_gpt":0.2385252123676362,"score_spread":0.1632136553039029,"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."}}