{"id":"W4247181703","doi":"10.32920/ryerson.14654040.v1","title":"Aperio: managing 3D scene occlusion using a mechanical tool analogy for visualizing multi-partmesh data.","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Strong","keywords":"Computer science; Polygon mesh; Visualization; Rendering (computer graphics); Computer graphics (images); Context (archaeology); Bridging (networking); Computer vision; Artificial intelligence","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":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001287238,0.0004795359,0.0006879327,0.0004884629,0.000381845,0.001428688,0.003314735,0.0003919677,0.00002071694],"category_scores_gemma":[0.000102433,0.0005027371,0.0002555605,0.0005933593,0.00003910035,0.0006226194,0.01993604,0.0004164125,0.00000122608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001186769,"about_ca_system_score_gemma":0.0004057385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002833235,"about_ca_topic_score_gemma":0.0001493035,"domain_scores_codex":[0.9958866,0.0002061197,0.0008353928,0.002033863,0.0004403568,0.0005976883],"domain_scores_gemma":[0.9960564,0.0001584397,0.0003678327,0.002850165,0.0004162392,0.0001509731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003524535,0.001064951,0.0002600745,0.001395053,0.0005411009,0.0002460764,0.001265749,0.001378242,0.006369708,0.8487585,0.002371849,0.1363135],"study_design_scores_gemma":[0.0003219271,0.00005440384,0.00002755626,0.0003413274,0.00003434573,0.00003416374,0.0000225839,0.9898721,0.001651206,0.004792404,0.002225354,0.0006226225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00137859,0.0003356036,0.9950984,0.0001778645,0.001234539,0.0008573849,0.00003226858,0.0008563893,0.00002903211],"genre_scores_gemma":[0.05263616,0.0003001195,0.9449691,0.00121924,0.0002011618,0.00004597605,0.0005477202,0.00005464784,0.00002589929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9884939,"threshold_uncertainty_score":0.9997424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1224094672687811,"score_gpt":0.3962147369055399,"score_spread":0.2738052696367588,"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."}}