{"id":"W4403821479","doi":"10.48550/arxiv.2410.00838","title":"Better Boosting of Communication Oracles, or Not","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Boosting (machine learning); Computer science; Artificial intelligence","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":[0.01543148,0.00147068,0.002695231,0.0007780953,0.001745892,0.004434251,0.003603136,0.003671586,0.009715677],"category_scores_gemma":[0.05058301,0.00123375,0.001693019,0.001225349,0.004057607,0.02279589,0.005969882,0.009140537,0.004029369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002358415,"about_ca_system_score_gemma":0.002640345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001428417,"about_ca_topic_score_gemma":0.001052803,"domain_scores_codex":[0.9853196,0.005570321,0.0005833025,0.003368876,0.0031443,0.002013596],"domain_scores_gemma":[0.9555264,0.01878613,0.001561425,0.01991915,0.00287656,0.001330357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001359721,0.0007469368,0.002516091,0.0004376119,0.0001123211,0.0001332416,0.0005336762,0.04585569,0.01470648,0.8106853,0.02114661,0.1017664],"study_design_scores_gemma":[0.0003228702,0.0003797856,0.001175166,0.0001077032,0.0001121036,0.0002978045,0.000138588,0.3626869,0.0205233,0.590952,0.0232144,0.00008942922],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06751088,0.001989976,0.8810418,0.01162088,0.0006543678,0.0002791301,0.0003399883,0.004988826,0.03157409],"genre_scores_gemma":[0.7214285,0.0008829217,0.255514,0.004691278,0.001154484,0.0004730172,0.0005581509,0.0009925578,0.01430506],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01543148,"threshold_uncertainty_score":0.08161044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1017879772693964,"score_gpt":0.2147237305778385,"score_spread":0.1129357533084421,"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."}}