{"id":"W4367848884","doi":"10.32920/22734338.v1","title":"ImmerVol: An Immersive Volume Visualization System","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Visualization; Volume rendering; Computer science; Rendering (computer graphics); Computer graphics (images); Opacity; Artificial intelligence; Computer vision; Physics","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":[0.0008663648,0.0008705877,0.0006612927,0.00083159,0.0002524415,0.001231074,0.001761059,0.0006735015,0.02087299],"category_scores_gemma":[0.002084371,0.000730869,0.0007400989,0.0004266792,0.0003088061,0.001474088,0.003375655,0.00108161,0.003978665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002323585,"about_ca_system_score_gemma":0.0004193244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009134606,"about_ca_topic_score_gemma":0.001322499,"domain_scores_codex":[0.9996458,0.00006392242,0.0000254053,0.00006437255,0.0001694759,0.00003105142],"domain_scores_gemma":[0.9994096,0.0002308081,0.000030937,0.0001476676,0.0001067992,0.0000742705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002168178,0.0005441579,0.002865127,0.001018976,0.0004664153,0.001285765,0.00127818,0.02208876,0.194392,0.0203679,0.230616,0.5229085],"study_design_scores_gemma":[0.001367185,0.001015922,0.007451317,0.0002597847,0.0002158108,0.003045295,0.0003479703,0.4209167,0.1059968,0.03282896,0.4260409,0.0005134096],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01755685,0.0005139424,0.7843222,0.0003277907,0.0002591243,0.0003399243,0.006626755,0.1802834,0.009769972],"genre_scores_gemma":[0.2711072,0.001212288,0.6595307,0.001097847,0.000290418,0.001216511,0.02374176,0.02182141,0.01998187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02087299,"threshold_uncertainty_score":0.06982708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04448220778484526,"score_gpt":0.3263207212191631,"score_spread":0.2818385134343178,"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."}}