{"id":"W4401769635","doi":"10.18280/isi.290434","title":"Candidate Best Optimizations Sequences for Code Size Reduction","year":2024,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reduction (mathematics); Code (set theory); Computer science; Mathematics; Programming language; Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0005631,0.0002701216,0.0002303586,0.0002362616,0.000728971,0.002838505,0.0004766807,0.000211353,0.0001073912],"category_scores_gemma":[0.0002899496,0.0002648933,0.0001215459,0.0008552489,0.0002593055,0.01600972,0.0001829126,0.0001934274,0.0003007068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004385657,"about_ca_system_score_gemma":0.0005517728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005559534,"about_ca_topic_score_gemma":0.00003410133,"domain_scores_codex":[0.9980634,0.00007428676,0.000752598,0.0003216254,0.0003231216,0.0004649669],"domain_scores_gemma":[0.9984831,0.0002233779,0.0002333882,0.0004186277,0.0004942036,0.0001473403],"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":[0.00002582318,0.00005053364,0.000009600023,0.001952443,0.00009691007,0.000008588609,0.01722027,0.03074104,0.0001787846,0.1489733,0.02109079,0.7796519],"study_design_scores_gemma":[0.0001965282,0.0001649601,0.00002704766,0.001305946,0.00005400204,0.0002288068,0.0007255942,0.7335013,0.000491125,0.01127008,0.2517341,0.0003005258],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001248607,0.006003312,0.9763334,0.002017749,0.008745578,0.0007025346,0.0009430134,0.0003591175,0.003646675],"genre_scores_gemma":[0.3908988,0.004704654,0.581133,0.0005061383,0.002615579,0.000753529,0.002160944,0.00008378852,0.01714358],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7793514,"threshold_uncertainty_score":0.9999803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02719312972631786,"score_gpt":0.2754569559368548,"score_spread":0.248263826210537,"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."}}