{"id":"W4410256283","doi":"10.1101/2025.05.06.652367","title":"Adaptation in somatosensory afferents improves rate and temporal coding of vibrotactile stimulus features","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Visual perception and processing mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Somatosensory system; Stimulus (psychology); Coding (social sciences); Psychology; Neuroscience; Cognitive psychology; Computer science; Mathematics; Statistics","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":[0.00015374,0.0002709306,0.0002968453,0.0001113902,0.0000621197,0.0002320253,0.0002534788,0.0002170878,0.001032762],"category_scores_gemma":[0.0006916592,0.0001233901,0.0002697504,0.00009144419,0.0001387376,0.0002880185,0.0003215714,0.0004609404,0.0001292518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001746194,"about_ca_system_score_gemma":0.0001723625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005410134,"about_ca_topic_score_gemma":0.0006643055,"domain_scores_codex":[0.9998995,0.000009712984,0.00001306991,0.00002185832,0.00002576712,0.00003005324],"domain_scores_gemma":[0.9998037,0.00004767374,0.00004257038,0.00002929734,0.00003462984,0.00004209047],"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":[0.00003940556,0.00001255023,0.0001889886,0.00001539484,0.000002318707,0.000009503446,0.000003726909,0.0001077679,0.998441,0.00001784438,0.000003403176,0.001158052],"study_design_scores_gemma":[0.00003098688,0.0009759775,0.1056096,0.00001341414,0.00005153536,0.0002350192,0.00004136728,0.01349442,0.8785545,0.0002721231,0.0006983632,0.00002272272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956855,0.0001972098,0.003640753,0.00002726607,0.00001359661,0.00001213563,0.00004514261,0.00004474703,0.0003336488],"genre_scores_gemma":[0.997799,0.0001439617,0.001581475,0.00003794813,0.000007011582,0.00001336648,0.00004050996,0.00001250014,0.000364157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001032762,"threshold_uncertainty_score":0.003454983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03481770286140425,"score_gpt":0.2752603736140983,"score_spread":0.240442670752694,"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."}}