{"id":"W4388919478","doi":"10.1007/978-981-99-6141-2_14","title":"em-Test for Higher Order","year":2023,"lang":"en","type":"book-chapter","venue":"ICSA book series in statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Presentation (obstetrics); Extension (predicate logic); Test (biology); Limiting; Range (aeronautics); Computer science; Null hypothesis; Null (SQL); Order (exchange); Likelihood-ratio test; Mathematics; Applied mathematics; Statistics; Engineering; Data mining; Mechanical engineering; Programming language; Ecology; Biology; Economics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003253238,0.0004373847,0.0005623687,0.0001838285,0.0001010873,0.0001829884,0.000823897,0.0003972275,0.0001532595],"category_scores_gemma":[0.0001776974,0.0004492164,0.00008217055,0.00008865242,0.0001488958,0.0003187158,0.0003494987,0.0004117541,0.00009902317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008541653,"about_ca_system_score_gemma":0.0002225439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000599694,"about_ca_topic_score_gemma":0.0001374033,"domain_scores_codex":[0.9980081,0.00002436468,0.0005433362,0.0006672911,0.000317145,0.0004397968],"domain_scores_gemma":[0.9976032,0.0009338093,0.0002371827,0.0008325832,0.0002825912,0.000110667],"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":[0.000007742897,0.000009579,9.723925e-7,0.0001161435,0.00002209662,0.0001007592,0.0001953022,0.000004101688,0.000002078948,0.9108717,0.0520131,0.0366564],"study_design_scores_gemma":[0.00014575,0.00009422634,0.000006533526,0.00007608946,0.00001508531,0.000005223701,0.000001331089,0.0007867317,0.000006103131,0.5295464,0.4690077,0.0003088049],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[2.129226e-8,0.0003369928,0.8337037,0.0003086087,0.001604516,0.0004049952,0.001142544,0.0001709823,0.1623276],"genre_scores_gemma":[5.877858e-7,0.0004688062,0.5019442,0.000423795,0.0001593366,0.00003611746,0.00006455951,0.00007042519,0.4968322],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4169946,"threshold_uncertainty_score":0.999796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03627644799870371,"score_gpt":0.2964858977363398,"score_spread":0.260209449737636,"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."}}