{"id":"W2767031149","doi":"10.1145/3126594.3126598","title":"HapticClench","year":2017,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Perception; Computer vision; Artificial intelligence; Human–computer interaction; Psychology; Neuroscience","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000005304865,0.00002667299,0.00002660553,0.00001206922,0.0004143327,0.0001307838,0.0001683073,0.00001114303,0.00117797],"category_scores_gemma":[0.0003795908,0.00002127632,0.00002024641,0.000006561717,0.00003857205,0.0002497167,0.00002687427,0.00004442271,0.001744273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003724374,"about_ca_system_score_gemma":0.000004049848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003169252,"about_ca_topic_score_gemma":0.00001493546,"domain_scores_codex":[0.9997392,0.000005885111,0.00003595574,0.00009587185,0.00005076797,0.00007233838],"domain_scores_gemma":[0.9995718,0.00004143167,0.00002560489,0.0003282714,0.000005954681,0.00002696423],"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":[0.00000319374,0.00002491642,0.0004630114,5.982472e-7,6.675921e-7,0.00001789813,0.00004595386,8.715894e-7,0.9502038,0.04013991,0.004278089,0.004821076],"study_design_scores_gemma":[0.00005825859,0.00001052354,0.003169118,0.000001377752,0.000001160306,0.00001568007,0.00001958512,0.0003206054,0.9079577,0.0007265068,0.08767571,0.00004379888],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3844744,1.266385e-7,0.00009026238,0.001137137,0.0003165604,0.00001862477,8.085643e-7,0.00003878343,0.6139234],"genre_scores_gemma":[0.9578815,0.000002480117,0.00005007494,0.00063914,0.00004449343,0.000001417836,2.747905e-8,0.000002504962,0.04137843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5734071,"threshold_uncertainty_score":0.9997351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1005275382357916,"score_gpt":0.3462049018460895,"score_spread":0.2456773636102978,"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."}}