{"id":"W2061739488","doi":"10.1145/1731903.1731943","title":"The Haptic Tabletop Puck","year":2009,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Haptic technology; Computer science; Focus (optics); Human–computer interaction; Stereotaxy; Visualization; Computer graphics (images); Computer vision; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003504049,0.0006370494,0.0004859503,0.0005439457,0.0005179059,0.001207941,0.001107279,0.0009705593,0.02319182],"category_scores_gemma":[0.001942259,0.0003411441,0.0003153368,0.0004123857,0.0006212246,0.00162915,0.001717955,0.0006179729,0.002563631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001632423,"about_ca_system_score_gemma":0.0003369621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007058363,"about_ca_topic_score_gemma":0.0005582118,"domain_scores_codex":[0.9995261,0.00006660774,0.00002437666,0.00009339896,0.0002375034,0.00005192757],"domain_scores_gemma":[0.9994065,0.0002561881,0.00003425664,0.0001256725,0.00009803582,0.00007933385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001912406,0.0002635668,0.001749523,0.001707888,0.00005530992,0.001873577,0.0009971469,0.003863791,0.3144738,0.02549924,0.03585601,0.6117477],"study_design_scores_gemma":[0.0006054234,0.004908386,0.02097478,0.0008005761,0.0002239503,0.01356479,0.001060935,0.07401751,0.1954492,0.01280089,0.6750435,0.0005499766],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1688425,0.006123849,0.6788389,0.001644384,0.001678001,0.002022864,0.002239769,0.01304592,0.1255638],"genre_scores_gemma":[0.6621881,0.002024533,0.2811429,0.0006738823,0.0001937905,0.0007800884,0.0007330434,0.0004167155,0.05184701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02319182,"threshold_uncertainty_score":0.07758433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03777947547502715,"score_gpt":0.2894389304017088,"score_spread":0.2516594549266817,"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."}}