{"id":"W2765580993","doi":"","title":"Building a Better Tor Experimentation Platform from the Magic of Dynamic ELFs","year":2017,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"MAGIC (telescope); Computer science; Physics; Astronomy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005647232,0.00084962,0.0007483728,0.0009802814,0.00121644,0.00223084,0.003136311,0.001307326,0.0131755],"category_scores_gemma":[0.009784698,0.000683533,0.001029251,0.0004542168,0.001790134,0.005973774,0.004103441,0.004012084,0.00489351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170732,"about_ca_system_score_gemma":0.001662783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002359914,"about_ca_topic_score_gemma":0.002780249,"domain_scores_codex":[0.9969433,0.001045124,0.0001792471,0.0004980365,0.0009261137,0.0004082048],"domain_scores_gemma":[0.9952938,0.00139959,0.0002200432,0.001655635,0.0008052546,0.0006255923],"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":[0.005139087,0.002904235,0.01709179,0.002790407,0.0005803515,0.003119799,0.003552566,0.1171686,0.160074,0.2088374,0.2087416,0.2700002],"study_design_scores_gemma":[0.000895477,0.001732196,0.006586013,0.0005465636,0.0001822039,0.0009122834,0.001045431,0.3202086,0.08748824,0.07348087,0.506414,0.000508194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08001994,0.0008265903,0.7156154,0.005316287,0.00241624,0.003325669,0.004436979,0.1248632,0.06317968],"genre_scores_gemma":[0.3342181,0.0009579231,0.6140366,0.003248915,0.0003948856,0.004527077,0.007938906,0.01406762,0.02061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0131755,"threshold_uncertainty_score":0.04407638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248718088674559,"score_gpt":0.242954249283574,"score_spread":0.2304670683968284,"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."}}