{"id":"W2148718790","doi":"10.1109/toh.2009.5","title":"Fast Calibration of Haptic Texture Synthesis Algorithms","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Haptics","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Haptic technology; Algorithm; Computer science; Surface finish; Equivalence (formal languages); Computer vision; Artificial intelligence; Mathematics; Engineering","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":[0.00002612878,0.0001659715,0.0001881108,0.0001975093,0.0002051545,0.00004208647,0.0001573958,0.0001125417,0.0002811227],"category_scores_gemma":[0.00005053278,0.0001582641,0.0001499215,0.0003050986,0.00007440603,0.0003033465,4.055197e-7,0.0003021765,0.00008855413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004295865,"about_ca_system_score_gemma":0.00003304948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001344891,"about_ca_topic_score_gemma":0.00001037183,"domain_scores_codex":[0.9988649,0.00006907728,0.0003002018,0.0002825163,0.0002769639,0.0002062755],"domain_scores_gemma":[0.9990351,0.0004023408,0.0001010072,0.0003253965,0.00004908189,0.00008710216],"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":[0.00008494283,0.0007054271,0.000001232038,0.00001287849,0.00001778719,0.00001818405,0.0004440623,0.02007358,0.9075399,0.0007081794,0.0003509222,0.07004291],"study_design_scores_gemma":[0.0001461544,0.0002149406,0.00001734637,0.00002853221,0.00006050964,0.0000456355,0.00009667569,0.09275168,0.9056426,0.0001662552,0.0006728618,0.0001568652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.031988,0.000003837382,0.9602576,0.001311315,0.0009146613,0.0002485689,0.0001575729,0.0001969199,0.004921482],"genre_scores_gemma":[0.9965208,0.00004896301,0.0007716275,0.0006401688,0.0000526552,0.00001167272,6.079678e-7,0.00001733449,0.00193619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9645328,"threshold_uncertainty_score":0.6453821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03445138047139726,"score_gpt":0.2718641038859918,"score_spread":0.2374127234145945,"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."}}