{"id":"W2921058353","doi":"10.1145/3361525.3361539","title":"Pando","year":2019,"lang":"en","type":"article","venue":"","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"PlanetLab; Rendering (computer graphics); Grid; Private network; Leverage (statistics); Testbed","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008415693,0.00005287546,0.00006732133,0.00005849934,0.00001575368,0.00006259615,0.001026195,0.00003230358,0.00004169286],"category_scores_gemma":[0.00001586176,0.00004149017,0.00001912101,0.0003133694,0.000007383755,0.0001563853,0.0004759791,0.0000525262,0.003889925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001266475,"about_ca_system_score_gemma":0.00001087935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008375202,"about_ca_topic_score_gemma":0.000003267239,"domain_scores_codex":[0.9994292,0.000005658447,0.00006119077,0.000201918,0.0001234917,0.0001784884],"domain_scores_gemma":[0.9992746,0.00002964083,0.00001111873,0.0006380989,0.00001350651,0.00003305803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001977786,0.00002270133,0.01042857,0.00000293753,0.000009491997,0.000009010329,0.0001232096,0.0001214412,0.002346078,0.5266835,0.1089341,0.351317],"study_design_scores_gemma":[0.0006440412,0.0003299824,0.02711068,0.00002267463,0.000002307961,0.0000300816,0.00004863552,0.05993149,0.02929688,0.05283625,0.8290759,0.0006710142],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1435667,0.00003880425,0.6941593,0.0101688,0.0005858503,0.0001860684,1.372045e-7,0.002276997,0.1490174],"genre_scores_gemma":[0.825205,0.000001598543,0.1625574,0.001148383,0.00001364105,0.000005181152,1.31901e-7,0.000002845746,0.0110658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7201418,"threshold_uncertainty_score":0.9968857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005171175364419993,"score_gpt":0.2034283309333506,"score_spread":0.1982571555689306,"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."}}