{"id":"W3129669023","doi":"10.1111/cgf.14330","title":"Data to Physicalization: A Survey of the Physical Rendering Process","year":2021,"lang":"en","type":"preprint","venue":"Computer Graphics Forum","topic":"Architecture and Computational Design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Calgary","funders":"","keywords":"Rendering (computer graphics); Computer science; Scope (computer science); Process (computing); Data science; Human–computer interaction; Computer graphics (images)","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":[],"consensus_categories":[],"category_scores_codex":[0.000128581,0.0002344828,0.0003280112,0.00008007599,0.00006255248,0.00006776356,0.00132785,0.00009216018,0.000001190877],"category_scores_gemma":[0.00002177891,0.0001974408,0.0001108726,0.000623613,0.00004252704,0.00005686745,0.002047736,0.0004463792,0.000001245469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001311561,"about_ca_system_score_gemma":0.00009754018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000209472,"about_ca_topic_score_gemma":0.0001144434,"domain_scores_codex":[0.9987073,0.00008688059,0.0002440761,0.0004146589,0.000345839,0.0002012775],"domain_scores_gemma":[0.998416,0.0001267821,0.0000663418,0.001135494,0.0001961344,0.00005924093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004075612,0.00005621002,0.0009740471,0.0003773742,0.0001758743,0.00000197151,0.0007194399,0.9895877,0.00003465889,0.001276672,0.002822187,0.003969746],"study_design_scores_gemma":[0.00006108918,0.00001399937,0.03420428,0.0002335469,0.0000247888,0.000002411388,0.000007396966,0.9595211,0.0002684182,0.005213107,0.0002147527,0.0002351869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1118316,0.0001345601,0.8862802,0.0001543308,0.0008850729,0.0002797332,0.0002516337,0.0001260248,0.00005681294],"genre_scores_gemma":[0.996934,0.000007599577,0.001951842,0.0001803261,0.0002382072,0.00001727107,0.0006261206,0.00004222586,0.000002402701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8851024,"threshold_uncertainty_score":0.8051403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05616219965503558,"score_gpt":0.284154705200821,"score_spread":0.2279925055457855,"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."}}