{"id":"W4386737341","doi":"10.1109/mcg.2023.3286228","title":"First Insights Into INTUIT: An INteractive Tactile Physicalization for User Interpretation of RADAR Technology","year":2023,"lang":"en","type":"article","venue":"IEEE Computer Graphics and Applications","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Mount Royal University","funders":"Campus France; Ministère de l'Europe et des Affaires Étrangères","keywords":"Radar; Computer science; Remote sensing; Augmented reality; Radar imaging; Geology; Artificial intelligence; Telecommunications","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":[0.00133349,0.001328036,0.0003978843,0.0005834402,0.0004536069,0.002619907,0.001310852,0.001148209,0.01826122],"category_scores_gemma":[0.005189796,0.0004009177,0.000721796,0.000263005,0.001227956,0.002963217,0.002446335,0.001324511,0.002342688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004869535,"about_ca_system_score_gemma":0.0003514857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001258238,"about_ca_topic_score_gemma":0.002584497,"domain_scores_codex":[0.9994215,0.0002526678,0.00002052059,0.00006907606,0.0001570228,0.00007926427],"domain_scores_gemma":[0.9982979,0.001159674,0.0000407943,0.0001476134,0.0002460227,0.0001080898],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002021156,0.001074884,0.008892597,0.003060796,0.0001318282,0.002837444,0.03513215,0.01560003,0.2382092,0.04218667,0.04824109,0.6026121],"study_design_scores_gemma":[0.0003480444,0.004144359,0.02848612,0.00164181,0.0002981866,0.006063415,0.01763316,0.2543018,0.1224607,0.05186827,0.5122105,0.0005436283],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1194061,0.001682237,0.8240058,0.002432024,0.0003482951,0.000871156,0.0008776662,0.0085898,0.0417869],"genre_scores_gemma":[0.4466105,0.001860338,0.5211936,0.0009927477,0.0001618002,0.0009647254,0.0008499721,0.0019174,0.02544901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01826122,"threshold_uncertainty_score":0.06108987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087398871227515,"score_gpt":0.259436864229823,"score_spread":0.2485628755175479,"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."}}