{"id":"W3109634409","doi":"10.3389/fcomp.2020.534974","title":"I can feel it moving: Science Communicators Talking About the Potential of Mid-Air Haptics","year":2020,"lang":"en","type":"article","venue":"Frontiers in Computer Science","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"H2020 European Research Council; Natural Sciences and Engineering Research Council of Canada; European Commission","keywords":"Haptic technology; Flexibility (engineering); Science communication; Thematic analysis; Domain (mathematical analysis); Science education; Constructive; Multimedia; Computer science; Human–computer interaction; Psychology; Qualitative research; Simulation; Mathematics education; Sociology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003692522,0.0001590411,0.0002147415,0.0003166705,0.0009330704,0.0002450706,0.003562495,0.00003582134,0.000006251554],"category_scores_gemma":[0.0005068035,0.0001286094,0.00007532766,0.002735257,0.003838675,0.0007816483,0.0009306973,0.0004149811,0.000006601958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001356759,"about_ca_system_score_gemma":0.0004431537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006775724,"about_ca_topic_score_gemma":0.0000117262,"domain_scores_codex":[0.997468,0.0001020587,0.0003767172,0.0006360884,0.000887209,0.000529918],"domain_scores_gemma":[0.9985639,0.000147969,0.000209076,0.0007596443,0.0001171878,0.0002021509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005781095,0.0002320743,0.007776807,0.00003925925,0.000008935835,0.00007350562,0.01675137,0.04883222,0.8771492,0.002667829,0.004297743,0.0421133],"study_design_scores_gemma":[0.0002751591,0.0001159469,0.0048899,0.00005114924,0.000008879918,0.00003953015,0.001002628,0.7384165,0.2522237,0.0004407172,0.002274407,0.0002614655],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7791272,0.00003531566,0.1989845,0.01496682,0.005329792,0.000335434,0.00001505775,0.00008991011,0.001115994],"genre_scores_gemma":[0.9795641,0.00003061998,0.01627118,0.004012235,0.00009010993,0.000003757836,2.12787e-7,0.000009159434,0.00001860837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6895843,"threshold_uncertainty_score":0.9988723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0332508085158196,"score_gpt":0.2712195511148225,"score_spread":0.2379687425990029,"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."}}