{"id":"W4312158865","doi":"10.1016/j.isci.2022.105874","title":"Modeling foot sole cutaneous afferents: FootSim","year":2022,"lang":"en","type":"article","venue":"iScience","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"H2020 European Research Council; European Research Council; Medical Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Commission; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Wellcome Trust","keywords":"Microneurography; Mechanoreceptor; Neuroscience; Afferent; Electrophysiology; Computer science; Functional electrical stimulation; Population; Sensory system; Stimulation; Biology; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004478316,0.00009546414,0.00008595605,0.000104111,0.001089597,0.00008881643,0.0005383317,0.00001439254,0.0005774299],"category_scores_gemma":[0.0002199444,0.00009401031,0.00005770614,0.0004206556,0.00007233088,0.0002646449,0.0002430785,0.000271677,0.0001368667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008572144,"about_ca_system_score_gemma":0.00005572297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006711181,"about_ca_topic_score_gemma":0.00001694586,"domain_scores_codex":[0.9985169,0.0000787638,0.0001481301,0.0004419358,0.0004834266,0.0003309053],"domain_scores_gemma":[0.9994398,0.000119129,0.00004201362,0.0002970389,0.00001877567,0.00008327853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002445128,0.0001612803,0.00003971681,0.000002581573,0.00000124564,0.0001255877,0.00111426,0.1814159,0.8086104,0.002273295,0.0008453671,0.005385954],"study_design_scores_gemma":[0.0001752243,0.0002221869,0.000007363041,0.000005819383,0.000006373764,0.00108804,0.001740629,0.8054571,0.1610584,0.00143605,0.02850357,0.0002992517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9680849,0.00001147771,0.002574041,0.0006005639,0.001281838,0.0001250418,0.00002322013,0.0001419494,0.02715694],"genre_scores_gemma":[0.9936191,0.000005878578,0.00006369947,0.00118918,0.00004368382,0.00003086991,5.787719e-7,0.00001010683,0.005036853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.647552,"threshold_uncertainty_score":0.8380406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06554523568161806,"score_gpt":0.3009967731875894,"score_spread":0.2354515375059713,"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."}}