{"id":"W2609313589","doi":"","title":"Conditional expectation algorithms for covering arrays","year":2014,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.003270339,0.001506364,0.002381893,0.001647636,0.001094815,0.002947875,0.004134814,0.002234936,0.009590311],"category_scores_gemma":[0.02905121,0.001153294,0.001563631,0.003576285,0.001961365,0.007899496,0.004196852,0.00442539,0.002199959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001990351,"about_ca_system_score_gemma":0.002360111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002197654,"about_ca_topic_score_gemma":0.002566682,"domain_scores_codex":[0.9965326,0.001531358,0.0001956129,0.0006130389,0.0007104017,0.0004169146],"domain_scores_gemma":[0.9718685,0.02245838,0.0008049449,0.002806409,0.001500457,0.0005613138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005958172,0.000410457,0.001712101,0.0003141757,0.0001621269,0.0001478064,0.0003119374,0.3685736,0.002358551,0.3830213,0.02005482,0.2223372],"study_design_scores_gemma":[0.00004029584,0.00004051007,0.0001597788,0.00002385419,0.00001820257,0.00005681442,0.00003133195,0.7037076,0.0009692857,0.2935917,0.001343065,0.00001763668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01206638,0.0004033053,0.9821915,0.0007771119,0.00007324547,0.00005802848,0.0003354498,0.001140411,0.002954618],"genre_scores_gemma":[0.3855042,0.001028667,0.5958844,0.001058612,0.0005085723,0.0006298785,0.003828014,0.001198124,0.0103595],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009590311,"threshold_uncertainty_score":0.03208274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01725646595065485,"score_gpt":0.2662495331624527,"score_spread":0.2489930672117978,"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."}}