{"id":"W2950748145","doi":"10.48550/arxiv.1504.07336","title":"Information content of partially rank-ordered set samples","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Fields Institute for Research in Mathematical Sciences; University of Toronto","funders":"","keywords":"Simple random sample; Sampling (signal processing); Statistics; Ranking (information retrieval); Mathematics; Entropy (arrow of time); Rank (graph theory); Stratified sampling; Sampling design; Population; Systematic sampling; Computer science; Artificial intelligence; Combinatorics","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":[],"consensus_categories":[],"category_scores_codex":[0.0004134655,0.0002162831,0.0004438935,0.0001810966,0.00004753572,0.00003675079,0.0003255298,0.0002905029,0.00005187833],"category_scores_gemma":[0.000298786,0.0002273732,0.0001557263,0.0001848334,0.00006169519,0.000320231,0.0003190925,0.0002001571,0.00002286629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001399957,"about_ca_system_score_gemma":0.0002208411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004575051,"about_ca_topic_score_gemma":0.0001352805,"domain_scores_codex":[0.9989327,0.0001169925,0.0004413357,0.0002121708,0.0001216527,0.0001751011],"domain_scores_gemma":[0.9978466,0.0001103891,0.0007075727,0.0005593724,0.0006755693,0.0001004823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003972222,0.000196272,0.0054618,0.002158577,0.0004673149,0.0000192849,0.004867639,0.6371435,0.00004466021,0.3374359,0.01153789,0.000269987],"study_design_scores_gemma":[0.006560904,0.000303998,0.002307923,0.001331601,0.001002679,0.000009023213,0.008681308,0.5146686,0.0005986479,0.4573441,0.005503588,0.001687606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7407414,0.0000453982,0.2516873,0.00005284563,0.0006023923,0.0009485897,0.0004439101,0.0001630071,0.005315105],"genre_scores_gemma":[0.997569,0.00005888175,0.001389814,0.00001836717,0.00004501085,0.000001423211,0.0002391464,0.00001591331,0.0006624906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2568276,"threshold_uncertainty_score":0.9272009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2580490849922512,"score_gpt":0.2265080696399583,"score_spread":0.03154101535229295,"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."}}