{"id":"W4408727277","doi":"10.1109/tvcg.2025.3549869","title":"PantographHaptics: A Technique for Large-Surface Passive Haptic Interactions using Pantograph Mechanisms","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Waterloo; Intertek (Canada)","funders":"","keywords":"Computer science; Haptic technology; Pantograph; Human–computer interaction; Visualization; Simulation; Computer graphics (images); Artificial intelligence; Engineering; Engineering drawing","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007652566,0.0002922252,0.000264829,0.0008850793,0.001032305,0.0001994753,0.0001604198,0.0001548915,0.00003290991],"category_scores_gemma":[0.00001532218,0.0003038274,0.0002584308,0.001268327,0.00009330116,0.0003532142,0.000004872131,0.0003147964,0.000004062532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002927808,"about_ca_system_score_gemma":0.00004946846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003198928,"about_ca_topic_score_gemma":0.00006932463,"domain_scores_codex":[0.9982943,0.0001576084,0.0004216451,0.0005905489,0.0001947839,0.0003411223],"domain_scores_gemma":[0.998755,0.0005107771,0.0001427196,0.0002929856,0.000190684,0.0001077942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001312618,0.0008209931,0.00001841772,0.00009083479,0.0001226032,0.000005008778,0.0005833057,0.001553087,0.147903,0.8476832,0.0001839584,0.0009043599],"study_design_scores_gemma":[0.0006434421,0.0001992459,0.00001184763,0.0001522118,0.0001400141,0.00004088474,0.0002272663,0.6835206,0.3077779,0.004148589,0.002844874,0.0002931748],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009849676,0.000006437969,0.9871233,0.00007577657,0.001495237,0.0009482697,0.0001323913,0.0002690548,0.00009993354],"genre_scores_gemma":[0.9943455,0.0001656157,0.003051853,0.00201819,0.00003189194,0.0001536696,0.00000661658,0.0000365336,0.0001901548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9844958,"threshold_uncertainty_score":0.9999414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03716909051277941,"score_gpt":0.3270269776345954,"score_spread":0.289857887121816,"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."}}