{"id":"W3033735869","doi":"10.1016/j.procs.2020.04.304","title":"CoDeCoVe: A Novel System Level Co-Design & Co-Verification Framework","year":2020,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Correctness; Electronic system-level design and verification; Abstraction; High-level synthesis; Embedded system; Abstraction layer; Computation; System on a chip; Software; Programming language","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":[0.002235985,0.000404748,0.0004612998,0.0003130211,0.0005102631,0.001258213,0.005529323,0.0001874859,0.000004556375],"category_scores_gemma":[0.0003473913,0.0003922152,0.00009852879,0.002742599,0.0003892567,0.002040668,0.0005676023,0.0004292067,0.0005282776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003027859,"about_ca_system_score_gemma":0.0008930297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000110489,"about_ca_topic_score_gemma":4.569006e-7,"domain_scores_codex":[0.9950603,0.0001407113,0.000718083,0.001738958,0.00153132,0.0008105818],"domain_scores_gemma":[0.9965858,0.0003794883,0.0004377643,0.001432802,0.0005820719,0.0005820869],"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":[0.00006515435,0.0004393573,0.001213081,0.00123353,0.00006828325,0.00005734221,0.02751059,0.0033795,0.192166,0.688549,0.04066934,0.04464888],"study_design_scores_gemma":[0.0003286074,0.0002907301,0.0006155685,0.0002875885,0.000008004422,0.0001786307,0.00003442114,0.9345526,0.05750285,0.001545426,0.003840324,0.0008153045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004691458,0.00006558879,0.9936684,0.001086525,0.0006262403,0.001051249,0.00001315179,0.002340076,0.0006795788],"genre_scores_gemma":[0.3870935,0.000003335226,0.6113796,0.001101337,0.0002925953,0.00009221027,0.000002310099,0.00001945646,0.0000156466],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.931173,"threshold_uncertainty_score":0.999853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1333460722129266,"score_gpt":0.3229659653026943,"score_spread":0.1896198930897676,"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."}}