{"id":"W4405935996","doi":"10.23919/cnsm62983.2024.10814296","title":"5GProvGen: 5G Provenance Dataset Generation Framework","year":2024,"lang":"en","type":"article","venue":"","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Provenance; Computer science; Data science; Geology; Paleontology","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":[],"consensus_categories":[],"category_scores_codex":[0.002647719,0.001219248,0.0006461759,0.002817856,0.0008032718,0.002124191,0.002383036,0.001255823,0.006729629],"category_scores_gemma":[0.01047694,0.0005626314,0.001569822,0.002330782,0.0006001041,0.002281715,0.002653681,0.001963672,0.003813824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379617,"about_ca_system_score_gemma":0.00215487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0164757,"about_ca_topic_score_gemma":0.02507084,"domain_scores_codex":[0.9986916,0.0002761644,0.0001506135,0.0003555641,0.0004362506,0.00008989641],"domain_scores_gemma":[0.9976733,0.0006780025,0.0001558973,0.001007777,0.0003737769,0.000111214],"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":[0.001014031,0.0003608496,0.01756238,0.002163518,0.000663679,0.001680833,0.0008707945,0.1510822,0.01396868,0.0762034,0.5693945,0.1650352],"study_design_scores_gemma":[0.0005041629,0.0001611402,0.007980037,0.0003184678,0.0001066861,0.0009114127,0.0003891413,0.3752294,0.01371711,0.06948444,0.5309979,0.0002000225],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.01332284,0.001232575,0.3455517,0.001976909,0.0005725566,0.001805331,0.5007563,0.1260622,0.008719488],"genre_scores_gemma":[0.06251435,0.0006648271,0.2337036,0.0004971392,0.00006334844,0.0009857945,0.6966828,0.002852736,0.002035473],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0164757,"threshold_uncertainty_score":0.03275961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02311178286506924,"score_gpt":0.3117022809811999,"score_spread":0.2885904981161307,"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."}}