{"id":"W6911744200","doi":"10.5281/zenodo.15338910","title":"Reproduction Package for CAV 2025 Submission `Btor2-Select: Machine Learning Based Algorithm Selection for Hardware Model Checking'","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artifact (error); Selection (genetic algorithm); Reliability (semiconductor); Set (abstract data type); Scripting language; Software","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004548231,0.00225301,0.001587106,0.002442901,0.0007766529,0.004288299,0.004161894,0.002300945,0.5804061],"category_scores_gemma":[0.03522556,0.001545478,0.002229781,0.001743069,0.001044827,0.003244452,0.003825096,0.002971179,0.3906478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223569,"about_ca_system_score_gemma":0.002078305,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001879852,"about_ca_topic_score_gemma":0.002002173,"domain_scores_codex":[0.9947343,0.0008218967,0.0005686579,0.0009274652,0.002568315,0.0003794159],"domain_scores_gemma":[0.9817854,0.00638421,0.0008477076,0.005322852,0.005199214,0.0004606436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002472084,0.00003926953,0.0002680232,0.0003855438,0.00003118283,0.00009238648,0.00004752574,0.001110985,0.001519221,0.005489911,0.9418314,0.04893732],"study_design_scores_gemma":[0.0003615125,0.0001538294,0.0008653097,0.0003083484,0.00002978862,0.0003072773,0.00003960399,0.01419186,0.01045374,0.01450161,0.9586623,0.0001246907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"other","genre_scores_codex":[0.0008959263,0.0002179969,0.2162025,0.001174521,0.002555353,0.000401673,0.06237721,0.6798659,0.03630897],"genre_scores_gemma":[0.01931708,0.0003054154,0.1220243,0.001556441,0.001039099,0.001295178,0.1475935,0.5998822,0.1069868],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5804061,"threshold_uncertainty_score":0.5984998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0331512979972898,"score_gpt":0.2667247441690568,"score_spread":0.233573446171767,"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."}}