{"id":"W7084580690","doi":"10.1145/3721241.3733986","title":"Graphics4Science: Computer Graphics for Scientific Impacts","year":2025,"lang":"en","type":"article","venue":"","topic":"Nonlinear Differential Equations Analysis","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer graphics; Scientific visualization; Graphics software; Graphics; Software","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001473431,0.003430827,0.002382845,0.005136243,0.001526367,0.00637451,0.003918328,0.003870852,0.5263185],"category_scores_gemma":[0.01003222,0.001792805,0.002332317,0.005476882,0.001269739,0.005002437,0.006368297,0.005561382,0.2418827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287019,"about_ca_system_score_gemma":0.002255065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002746149,"about_ca_topic_score_gemma":0.003625244,"domain_scores_codex":[0.9980611,0.00023113,0.0001022556,0.0002694312,0.00116573,0.0001704046],"domain_scores_gemma":[0.9958044,0.001159145,0.0001415709,0.0006333653,0.001634778,0.0006268282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008474262,0.0000366283,0.0001657497,0.0002910992,0.00004892716,0.00008335675,0.00007824506,0.001368861,0.00247843,0.03416299,0.8644602,0.09674093],"study_design_scores_gemma":[0.0001742954,0.00003838021,0.0004527652,0.0002136261,0.00006183195,0.0001905377,0.00003650803,0.01775662,0.004421481,0.08480348,0.8917688,0.00008170672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001687801,0.00296379,0.4194009,0.006151644,0.008482342,0.0003551681,0.03347693,0.2406648,0.2868166],"genre_scores_gemma":[0.03634951,0.006715095,0.3338451,0.004310105,0.004252668,0.001753881,0.06482926,0.2180625,0.3298818],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5263185,"threshold_uncertainty_score":0.6756492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05630016496245049,"score_gpt":0.3660604170648163,"score_spread":0.3097602521023659,"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."}}