{"id":"W6967677459","doi":"10.5281/zenodo.10437041","title":"Toward Adaptive Tracing: Efficient System Behavior Analysis using Language Models","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Source code; Kernel (algebra); Data source; Key (lock); Code (set theory); Web server","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":[0.0004188784,0.0001034063,0.0001258313,0.0001628298,0.0007022398,0.000161477,0.000382716,0.00007469585,0.0001693963],"category_scores_gemma":[0.00007979287,0.0000944089,0.0001019032,0.0007671735,0.00005696063,0.000004984764,0.0007035731,0.00009251427,0.0003458751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004816113,"about_ca_system_score_gemma":0.000002306618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001056423,"about_ca_topic_score_gemma":1.417734e-7,"domain_scores_codex":[0.9988396,0.00018703,0.0001625619,0.0003664479,0.0001697432,0.0002746734],"domain_scores_gemma":[0.9994051,0.000005810489,0.00006397722,0.0002453102,0.0001855928,0.00009417651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002108988,0.0002889095,0.0000466311,0.0001172825,0.0006138048,0.000154501,0.002384295,0.2020727,0.7368215,0.001906596,0.003299734,0.05208315],"study_design_scores_gemma":[0.001274191,0.001168918,0.002400136,0.00008124609,0.0006508424,0.0002383757,0.009794764,0.9043594,0.03989759,0.00003340881,0.03906903,0.001032092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9391576,0.00007151502,0.05304079,0.00002028525,0.00004175134,0.0002043529,0.0001057742,0.0003518442,0.00700606],"genre_scores_gemma":[0.9980797,0.000006945905,0.0002911326,0.00001920056,0.00009566561,4.164015e-8,0.001177797,0.0002318579,0.00009768789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7022867,"threshold_uncertainty_score":0.5401132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07713998688621512,"score_gpt":0.2785133182458111,"score_spread":0.201373331359596,"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."}}