{"id":"W4391592471","doi":"10.1093/imaiai/iaad056","title":"Statistical inference with regularized optimal transport","year":2024,"lang":"en","type":"article","venue":"Information and Inference A Journal of the IMA","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Estimator; Consistency (knowledge bases); Statistical inference; Inference; Flexibility (engineering); Limit (mathematics); Mathematical optimization; Computer science; Smoothing; Mathematics; Probability distribution; Algorithm; Applied mathematics; Artificial intelligence; Statistics","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":[0.0105407,0.0009526196,0.001553629,0.002353589,0.0006641504,0.00227137,0.00251504,0.001806767,0.00259367],"category_scores_gemma":[0.05029707,0.0007955487,0.001420256,0.001704615,0.004060128,0.004952963,0.00322721,0.002854956,0.0003467453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002339291,"about_ca_system_score_gemma":0.002198277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004493972,"about_ca_topic_score_gemma":0.002487827,"domain_scores_codex":[0.9956402,0.002455041,0.0002693037,0.0007808949,0.0006622968,0.0001923294],"domain_scores_gemma":[0.9736634,0.01848803,0.002062331,0.003414882,0.001928185,0.000443145],"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":[0.00006589501,0.0000323767,0.001152797,0.0001071989,0.0000836398,0.0001330041,0.00008882038,0.2567526,0.0006673938,0.7253736,0.0008475661,0.01469518],"study_design_scores_gemma":[0.000008564908,0.00001827656,0.0002107578,0.00002129109,0.0000098978,0.00002885335,0.0000142553,0.6867645,0.000328301,0.3120743,0.000507762,0.00001319087],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01013636,0.0001847702,0.9883798,0.0002308038,0.00002340242,0.00002310219,0.00008764947,0.0001446318,0.0007894277],"genre_scores_gemma":[0.5379025,0.0006419866,0.4552415,0.0004176274,0.0002265987,0.0002918719,0.0006988135,0.000359984,0.004219259],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0105407,"threshold_uncertainty_score":0.05574518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03608366168691175,"score_gpt":0.3514610211691682,"score_spread":0.3153773594822564,"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."}}