{"id":"W1466377058","doi":"10.1017/cbo9780511611131.009","title":"Likelihood approximations","year":2007,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Approximations of π; Order (exchange); Mathematics; Applied mathematics; Calculus (dental); Mathematical economics; Computer science; Economics; Medicine","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":[0.0001134963,0.0003108546,0.0003000625,0.0002242315,0.0001261743,0.00005532038,0.001148974,0.0002678501,9.722096e-7],"category_scores_gemma":[0.00001639697,0.0003784174,0.0001551648,0.00001434214,0.00008058414,0.0002025164,0.0006666379,0.0004697595,0.00003097211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001876193,"about_ca_system_score_gemma":0.00005961083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004020075,"about_ca_topic_score_gemma":2.123647e-7,"domain_scores_codex":[0.9986578,0.00000746002,0.0002081809,0.0004847984,0.0003024584,0.0003392743],"domain_scores_gemma":[0.9985054,0.0001135307,0.0001369038,0.0009054877,0.0001427903,0.0001958488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002224501,0.000005984919,1.818149e-8,0.00006562044,0.00003203539,0.00008577491,0.00002887545,0.0002355866,0.00001269948,0.9958366,0.00100756,0.002687058],"study_design_scores_gemma":[0.0004134735,0.00004154299,7.820544e-7,0.0003531893,0.00009287343,0.00004397289,0.00000837468,0.1089764,0.0002771851,0.002631141,0.8861882,0.0009728366],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[8.563868e-7,0.00003134734,0.5004399,0.000004967324,0.0001085382,0.0001320492,0.000009855148,0.000311642,0.4989608],"genre_scores_gemma":[0.0001268023,0.00001645281,0.1491385,0.00004035819,0.00007293912,6.104158e-7,0.00000652169,0.00003808435,0.8505598],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9932054,"threshold_uncertainty_score":0.9998668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03126534258521851,"score_gpt":0.2173924486352958,"score_spread":0.1861271060500773,"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."}}