{"id":"W4399574028","doi":"10.32614/cran.package.jointcalib","title":"jointCalib: A Joint Calibration of Totals and Quantiles","year":2024,"lang":"en","type":"dataset","venue":"","topic":"Statistical and numerical algorithms","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Quantile; Calibration; Joint (building); Statistics; Mathematics; Econometrics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001343943,0.0002097572,0.0005473416,0.00008821369,0.00001970927,0.00004431677,0.00007951458,0.0001827478,0.001283047],"category_scores_gemma":[0.0004598259,0.0001397973,0.00008670463,0.0001158159,0.0001073946,0.00003496902,0.0001439377,0.0002129192,0.0001488192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009602844,"about_ca_system_score_gemma":0.00002856747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001829321,"about_ca_topic_score_gemma":0.00002724611,"domain_scores_codex":[0.9987658,0.00004289689,0.0005135399,0.0002722692,0.0002576509,0.000147805],"domain_scores_gemma":[0.9990079,0.000511957,0.0001168675,0.0002402311,0.00003360065,0.00008941657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005404961,0.00006800651,1.74851e-7,0.001397248,0.00005301955,0.00001680762,0.00001110527,2.968924e-8,0.0000196032,0.02282833,0.9749278,0.0006725091],"study_design_scores_gemma":[0.0001403247,0.0002211698,0.000007509721,0.0003830561,0.0002868116,0.00002854927,0.00003788635,0.00217198,0.0004499636,0.4658042,0.5301379,0.000330681],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002746114,0.0001891655,0.00685251,0.0002283425,0.0001814516,0.0001725967,0.9921521,0.00005442449,0.0001419416],"genre_scores_gemma":[0.00004291272,0.0003139536,0.02861976,0.0001451259,0.0002067897,0.00002916514,0.9697525,0.00003879956,0.0008509689],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4447899,"threshold_uncertainty_score":0.9996299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06756158926776032,"score_gpt":0.3334013959208788,"score_spread":0.2658398066531185,"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."}}