{"id":"W4312160046","doi":"10.1016/j.cnp.2022.12.001","title":"Investigating the intra-session reliability of short and long latency afferent inhibition","year":2022,"lang":"en","type":"article","venue":"Clinical Neurophysiology Practice","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability (semiconductor); Latency (audio); Afferent; Statistics; Medicine; Physical medicine and rehabilitation; Computer science; Mathematics; Internal medicine; Telecommunications","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":[0.003682947,0.0003508212,0.0004236804,0.0004616118,0.0002506731,0.0004853019,0.0003138632,0.0004100425,0.001593069],"category_scores_gemma":[0.01328877,0.0001406654,0.0001588475,0.0002945715,0.0003349958,0.000429965,0.000539611,0.000399285,0.0003465938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001394719,"about_ca_system_score_gemma":0.000217814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009123412,"about_ca_topic_score_gemma":0.001870618,"domain_scores_codex":[0.998669,0.0004120297,0.0001384781,0.0003577213,0.0003430574,0.00007964809],"domain_scores_gemma":[0.9921445,0.003428422,0.001261502,0.0008100499,0.002103906,0.0002516476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004111856,0.0004905919,0.6765197,0.00053874,0.0007867689,0.0002154959,0.0027583,0.001311404,0.1868644,0.0003204911,0.0009588612,0.1251234],"study_design_scores_gemma":[0.00002559476,0.001066562,0.9884309,0.00001870309,0.00008477191,0.0003160427,0.0002697308,0.001868347,0.007346521,0.000162007,0.0003890989,0.00002185052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881343,0.0004907063,0.008605817,0.00003612768,0.00004377698,0.00007840862,0.0003690002,0.00009991328,0.002141947],"genre_scores_gemma":[0.9972268,0.00005153423,0.002028587,0.00001834547,0.00002202156,0.00004670044,0.0001765961,0.00001765229,0.0004117675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003682947,"threshold_uncertainty_score":0.01947749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07284901700682213,"score_gpt":0.3818274724456959,"score_spread":0.3089784554388738,"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."}}