{"id":"W4311760592","doi":"10.1038/s41598-022-24640-5","title":"Texture recognition based on multi-sensory integration of proprioceptive and tactile signals","year":2022,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Proprioception; Neuromorphic engineering; Sensory system; Tactile sensor; Computer science; Artificial intelligence; Computer vision; Neuroscience; Artificial neural network; Psychology; Robot","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002805266,0.000105526,0.0001247802,0.0002893006,0.0006108693,0.00009417702,0.00006466098,0.00003242685,0.0008638916],"category_scores_gemma":[0.0007722274,0.00009514473,0.00006741245,0.0004101012,0.000166816,0.0002381833,0.00003730015,0.0002555764,0.00001577783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006079134,"about_ca_system_score_gemma":0.00008321678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000203391,"about_ca_topic_score_gemma":0.000009966828,"domain_scores_codex":[0.9982049,0.0001953452,0.0003229062,0.0006329153,0.0004968121,0.0001470934],"domain_scores_gemma":[0.9989217,0.0001728909,0.0003792258,0.0003548767,0.0001144422,0.00005684935],"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":[0.00004289926,0.0002593602,0.00008674976,0.000006811618,0.000001700289,0.0001050543,0.000630537,0.0006090149,0.9899088,0.000009215029,0.001779876,0.006559993],"study_design_scores_gemma":[0.0001298087,0.0001579735,0.0002345033,0.00002188088,0.00001048248,0.0001983524,0.0008383063,0.009725835,0.9813048,0.0005145875,0.006748786,0.0001147292],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926497,0.000003975463,0.0004487401,0.0001633142,0.003199283,0.0004713528,0.0000611748,0.0000599978,0.002942514],"genre_scores_gemma":[0.9954004,8.541217e-7,0.000198628,0.0001811639,0.00002010506,0.00005860903,0.00003383246,0.00001080521,0.004095609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00911682,"threshold_uncertainty_score":0.9459007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07161397730781476,"score_gpt":0.2997601046607337,"score_spread":0.2281461273529189,"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."}}