{"id":"W4298858096","doi":"10.48550/arxiv.1205.5819","title":"Measurability Aspects of the Compactness Theorem for Sample Compression Schemes","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Ottawa","keywords":"Compact space; Mathematics; Compression (physics); Linear subspace; Sample (material); Separable space; Scheme (mathematics); Sample space; Discrete mathematics; Subspace topology; Pure mathematics; Mathematical analysis; Statistics; Physics","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":[0.007861213,0.0008258582,0.001297943,0.001613642,0.001520121,0.003436985,0.001813017,0.001985981,0.005221389],"category_scores_gemma":[0.03578243,0.0007221127,0.001821408,0.00132306,0.009242623,0.01221392,0.007064662,0.004140424,0.0005538809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002241255,"about_ca_system_score_gemma":0.0007852431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005041744,"about_ca_topic_score_gemma":0.000266904,"domain_scores_codex":[0.9931393,0.002218881,0.0005137059,0.001463291,0.002195726,0.0004690675],"domain_scores_gemma":[0.9583109,0.02959966,0.00236953,0.006363363,0.002163985,0.001192458],"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":[0.0001337536,0.00004802183,0.001355578,0.0001629377,0.00005474065,0.0001166477,0.0005276485,0.007656735,0.00383899,0.9679829,0.0007430847,0.01737899],"study_design_scores_gemma":[0.00006832617,0.0002800878,0.002258629,0.0000666354,0.00004110537,0.0004255896,0.0001548008,0.08630192,0.01064038,0.8940765,0.005618265,0.00006772323],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1298206,0.001330353,0.8486599,0.002212536,0.00009199139,0.0001947721,0.0003297862,0.0004798935,0.01688009],"genre_scores_gemma":[0.8755103,0.0006793255,0.1163292,0.00055552,0.0003178575,0.0005521871,0.0004466843,0.0001606432,0.005448179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007861213,"threshold_uncertainty_score":0.04157454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1228202044450755,"score_gpt":0.2169972327893324,"score_spread":0.09417702834425692,"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."}}