{"id":"W4301391789","doi":"10.1109/tvcg.2022.3209365","title":"KiriPhys: Exploring New Data Physicalization Opportunities","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Visualization and Computer Graphics","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Simon Fraser University","funders":"","keywords":"Curiosity; Computer science; Data exploration; Data science; Human–computer interaction; Data visualization; Qualitative property; Visualization; World Wide Web; Artificial intelligence; Machine learning; Psychology","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":[0.002185781,0.0007096336,0.0003486892,0.001122685,0.002051083,0.003712612,0.001106217,0.001015121,0.007789041],"category_scores_gemma":[0.004941104,0.0004157261,0.0007264612,0.001188667,0.003688871,0.007216962,0.00798965,0.001194599,0.0006276629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005493732,"about_ca_system_score_gemma":0.0006008739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001029136,"about_ca_topic_score_gemma":0.003006428,"domain_scores_codex":[0.998481,0.0007511608,0.00006893963,0.0001595234,0.0003783105,0.0001611748],"domain_scores_gemma":[0.9975076,0.001622049,0.0001246146,0.0004776383,0.0001160044,0.0001520804],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001105032,0.0002028453,0.01577484,0.003581198,0.0001201558,0.005459813,0.491105,0.004202735,0.06120811,0.1947568,0.01915481,0.2033287],"study_design_scores_gemma":[0.0001119681,0.0004808173,0.02575407,0.001097554,0.0001250363,0.00728336,0.2180483,0.01229593,0.01682257,0.07005473,0.6475995,0.0003262602],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7629132,0.001897258,0.1506221,0.003006927,0.0002599235,0.0002817069,0.0008197209,0.001655328,0.07854383],"genre_scores_gemma":[0.8967202,0.0006593822,0.09118476,0.0003335413,0.00005499898,0.0002156279,0.0003849959,0.0003436684,0.01010282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007789041,"threshold_uncertainty_score":0.02605695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2220589424088418,"score_gpt":0.324794519415448,"score_spread":0.1027355770066062,"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."}}