{"id":"W2963616548","doi":"10.5555/3019129.3019131","title":"Devito: automated fast finite difference computation","year":2016,"lang":"en","type":"article","venue":"IEEE International Conference on High Performance Computing, Data, and Analytics","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Domain-specific language; Abstraction; Domain (mathematical analysis); Stencil; Theoretical computer science; Programming language; Code (set theory); Computation; Variety (cybernetics); Finite difference; Algorithm; Computational science; Artificial intelligence; Mathematics","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":[0.0002368828,0.0001841255,0.0001777925,0.0001730656,0.0001811103,0.0001592682,0.000642881,0.00006147162,0.0002713531],"category_scores_gemma":[0.00006110273,0.0001279196,0.00002170165,0.0001138131,0.0001690872,0.000364751,0.00006518428,0.0001395314,0.0001657099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001281362,"about_ca_system_score_gemma":0.00005827839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003306451,"about_ca_topic_score_gemma":0.00002155141,"domain_scores_codex":[0.9986523,0.00003869405,0.0002940919,0.0004175763,0.0003615813,0.0002357235],"domain_scores_gemma":[0.999065,0.0002257982,0.0001765323,0.0002669676,0.0001708856,0.00009474999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006796593,0.00005088923,0.1705824,0.00003285528,0.00006706833,0.00001105845,0.0001240514,0.003014582,0.0001795256,0.000582018,0.0128358,0.8124518],"study_design_scores_gemma":[0.000294782,0.0001156884,0.07462093,0.0002291574,0.00001013325,0.000009400348,0.00003020596,0.9222786,0.0003965659,0.0003942816,0.001425638,0.0001945532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940571,0.00002017448,0.05247307,0.001627055,0.001152738,0.00009594691,0.0006061812,0.0004189874,0.003034899],"genre_scores_gemma":[0.9958353,0.0005124234,0.001901465,0.0007847559,0.0001848595,2.819875e-7,0.0003984508,0.000004692228,0.0003777817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9192641,"threshold_uncertainty_score":0.5216412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05559194547291946,"score_gpt":0.293917855258952,"score_spread":0.2383259097860326,"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."}}