{"id":"W3016114008","doi":"10.1145/3313831.3376280","title":"Defining Haptic Experience: Foundations for Understanding, Communicating, and Evaluating HX","year":2020,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Haptic technology; Computer science; Usability; Human–computer interaction; Heuristics; User experience design; Timbre; Experiential learning; Personalization; Multimedia; Simulation; Psychology; World Wide Web","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":[0.00004411148,0.00007819729,0.00008815087,0.00003001209,0.0006972658,0.0001448657,0.0001401407,0.00002492284,0.0002232784],"category_scores_gemma":[0.00222566,0.00007483124,0.00003493808,0.0001222181,0.00009274668,0.0002589432,0.00006625662,0.0001158076,0.00003189861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000343644,"about_ca_system_score_gemma":0.00002508011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000184042,"about_ca_topic_score_gemma":0.00001881895,"domain_scores_codex":[0.9992692,0.00005504231,0.0001731848,0.0002351985,0.000113029,0.0001543458],"domain_scores_gemma":[0.9984189,0.001239506,0.00007488424,0.0001595599,0.00002246358,0.00008468189],"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":[0.00004955444,0.00005035853,0.0008071795,0.00002931224,0.00001020403,0.000001653964,0.0283781,0.0001151104,0.468429,0.4969799,0.001315194,0.003834408],"study_design_scores_gemma":[0.00125389,0.000709346,0.0001024223,0.00005004159,0.00005147265,0.00005645808,0.05339429,0.843403,0.07178631,0.00999925,0.01869532,0.0004981493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6374295,0.00004854403,0.2389172,0.01386783,0.0003822874,0.0009469045,0.00003080789,0.0005125847,0.1078644],"genre_scores_gemma":[0.9918714,0.00001089212,0.00487946,0.002884398,0.00002445089,0.00004822601,0.000002380725,0.00001157161,0.0002672666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8432879,"threshold_uncertainty_score":0.5362875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3728321011502986,"score_gpt":0.4325100693219568,"score_spread":0.05967796817165816,"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."}}