{"id":"W4396555758","doi":"10.1145/3662181","title":"IMESH: A DSL for Mesh Processing","year":2024,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Digital subscriber line; Computer science; Computer graphics (images); Computational science; Telecommunications","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":[0.003026652,0.001851831,0.00133726,0.001576043,0.0008682693,0.004263112,0.00576707,0.00214105,0.02717485],"category_scores_gemma":[0.00745119,0.001749508,0.002838925,0.001243709,0.00154238,0.004345174,0.005198072,0.005737056,0.01480155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515737,"about_ca_system_score_gemma":0.002382464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00219803,"about_ca_topic_score_gemma":0.003774294,"domain_scores_codex":[0.9971671,0.0004607073,0.000491173,0.0003625407,0.001332566,0.0001859336],"domain_scores_gemma":[0.9972287,0.0009397324,0.000208604,0.0007486921,0.0006756713,0.0001984887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003580569,0.0001251944,0.001345521,0.001547791,0.0001642347,0.0005418936,0.0009963452,0.04610366,0.02190439,0.4538895,0.2206534,0.2523699],"study_design_scores_gemma":[0.0001532489,0.00006959688,0.0002213757,0.0002131137,0.00004181641,0.0003966263,0.00008766838,0.1734631,0.01893218,0.09691442,0.7093959,0.0001109641],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0004675917,0.0001184955,0.9537958,0.0001679578,0.0001329463,0.00008367195,0.001996768,0.03872,0.004516745],"genre_scores_gemma":[0.0199597,0.0006119979,0.9267145,0.0008412693,0.0001961229,0.001087561,0.00937996,0.02964394,0.01156493],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02717485,"threshold_uncertainty_score":0.09090894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03389134941486909,"score_gpt":0.3236428621500467,"score_spread":0.2897515127351776,"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."}}