{"id":"W1974895834","doi":"10.1016/j.pt.2003.11.008","title":"Bayesian statistics for parasitologists","year":2003,"lang":"en","type":"review","venue":"Trends in Parasitology","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":75,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Montreal General Hospital","funders":"","keywords":"Frequentist inference; Bayesian probability; Bayesian statistics; Statistical inference; Ivermectin; Bayesian inference; Identification (biology); Inference; Onchocerciasis; Statistics; Computer science; Econometrics; Biology; Mathematics; Artificial intelligence; Ecology","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":[0.0006901815,0.0007760731,0.003919377,0.000748692,0.00008914871,0.00003820272,0.0005593799,0.001055541,0.0005637612],"category_scores_gemma":[0.001950449,0.0006493611,0.0004033745,0.0007094751,0.0003347076,0.00003356831,0.0000540214,0.0007006531,0.00004458374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001628574,"about_ca_system_score_gemma":0.0002016581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001129928,"about_ca_topic_score_gemma":0.0001314905,"domain_scores_codex":[0.995307,0.001059018,0.001571056,0.0009215736,0.0001934373,0.0009479484],"domain_scores_gemma":[0.9890321,0.009299536,0.0006670269,0.0007592041,0.0000728349,0.0001693076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007875217,0.00009043221,0.00005343893,0.003893433,0.00007329772,0.00009125857,0.00001208488,2.895043e-8,5.462427e-9,0.4021418,0.007122222,0.5865141],"study_design_scores_gemma":[0.0003184105,0.0001388139,0.00001917643,0.001175903,0.0007024648,0.0001811916,0.000003737786,0.00003340685,1.716178e-7,0.5018395,0.4950661,0.0005210701],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[5.784225e-8,0.4524859,0.5430949,0.0000118159,0.0006984464,0.0004138726,0.00064653,0.00005543862,0.002593086],"genre_scores_gemma":[4.912019e-7,0.4799979,0.5187446,0.00002131717,0.00009106521,0.0004688055,0.0001551631,0.0000696495,0.0004510195],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5859931,"threshold_uncertainty_score":0.9995958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2084902677881192,"score_gpt":0.5376510663029339,"score_spread":0.3291607985148147,"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."}}