{"id":"W2150746286","doi":"10.1109/vecims.2007.4373919","title":"A Device Independent Haptic Player","year":2007,"lang":"en","type":"article","venue":"","topic":"Motor Control and Adaptation","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Haptic technology; Computer science; Human–computer interaction; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002286694,0.0008714138,0.0009540329,0.0006708449,0.000423706,0.001974544,0.002992702,0.001265919,0.01168434],"category_scores_gemma":[0.006336555,0.0005077822,0.0004512061,0.0002746335,0.0008699918,0.002094646,0.002184487,0.0007916454,0.002218846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004845384,"about_ca_system_score_gemma":0.0007600124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006134994,"about_ca_topic_score_gemma":0.0005999611,"domain_scores_codex":[0.9973761,0.0005794339,0.0001924699,0.0004637123,0.001209172,0.0001791005],"domain_scores_gemma":[0.9952858,0.002279663,0.000268845,0.0009357975,0.0009722461,0.0002577134],"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":[0.004161463,0.0007718861,0.003641526,0.002355765,0.0002182437,0.001243502,0.001075271,0.005290316,0.6674232,0.00611731,0.003770499,0.3039309],"study_design_scores_gemma":[0.001245387,0.01010644,0.01826502,0.0003353614,0.0007971793,0.006079054,0.0005202178,0.1539212,0.7277834,0.002088318,0.07834443,0.0005140204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2714839,0.0006759397,0.702775,0.0002243708,0.0003238618,0.002032547,0.0006885635,0.01057636,0.01121951],"genre_scores_gemma":[0.5919145,0.0003342656,0.3879079,0.0003619806,0.00008162943,0.001113418,0.0006969214,0.0006374923,0.01695195],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01168434,"threshold_uncertainty_score":0.03908795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04308463214587261,"score_gpt":0.2772985091208713,"score_spread":0.2342138769749987,"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."}}