{"id":"W3135656960","doi":"10.1002/sta4.375","title":"Composite likelihood ratio testing under nonstandard conditions using tangent cones","year":2021,"lang":"en","type":"article","venue":"Stat","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Likelihood-ratio test; Monte Carlo method; Mixing (physics); Statistics; Parameter space; Statistic; Statistical hypothesis testing; Null hypothesis; Composite number; Projection (relational algebra); Null distribution; Null (SQL); Boundary (topology); Maximum likelihood; Test statistic; Applied mathematics; Mathematical analysis; Algorithm; Computer science; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02710411,0.001439916,0.001974069,0.00246581,0.0008805026,0.003748341,0.002858886,0.001550045,0.004676653],"category_scores_gemma":[0.1025912,0.001022685,0.001715631,0.002575907,0.004269317,0.005928537,0.003855435,0.004019392,0.001021922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001268119,"about_ca_system_score_gemma":0.002969438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001272395,"about_ca_topic_score_gemma":0.0009089425,"domain_scores_codex":[0.9790828,0.01360149,0.001187097,0.002193305,0.003446129,0.0004892071],"domain_scores_gemma":[0.9302589,0.05658479,0.004000427,0.003889744,0.00411016,0.001155935],"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":[0.000371412,0.0001226031,0.004805319,0.0002386379,0.0001372282,0.0008845915,0.0003097386,0.07823732,0.005045129,0.8361647,0.001584832,0.07209856],"study_design_scores_gemma":[0.00007558173,0.0001112071,0.0009674531,0.00004523166,0.00001999634,0.0003459115,0.00004992128,0.5623893,0.002861191,0.4314158,0.001659572,0.00005886485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004410189,0.00005827967,0.9947936,0.00005293354,0.00001458893,0.00004128165,0.00004299086,0.00009991203,0.0004862022],"genre_scores_gemma":[0.1280824,0.0002363794,0.8696272,0.0001343323,0.00007333519,0.0004184553,0.0003468024,0.0002171245,0.000863925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02710411,"threshold_uncertainty_score":0.143342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2037071763156445,"score_gpt":0.425003614604793,"score_spread":0.2212964382891486,"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."}}