{"id":"W4367596807","doi":"10.54846/jshap/1315","title":"A sounder of swine: The importance of clustering in the design, analysis, and interpretation of clinical trials","year":2023,"lang":"en","type":"article","venue":"Journal of Swine Health and Production","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"University of Guelph","keywords":"Cluster analysis; Statistics; Sample size determination; Confidence interval; Sample (material); Interpretation (philosophy); Clinical trial; Econometrics; Computer science; Mathematics; Medicine; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0126901,0.00006387378,0.0005987933,0.0001777598,0.00005474488,0.000005200503,0.00005816581,0.00003227257,0.000003188165],"category_scores_gemma":[0.001381989,0.00003357974,0.0001234127,0.0004668534,0.00008201077,0.00009417381,0.00002442249,0.0001661443,7.106818e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008965795,"about_ca_system_score_gemma":0.00006498872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006660493,"about_ca_topic_score_gemma":0.00004893231,"domain_scores_codex":[0.9971804,0.0008743177,0.001583327,0.0000986891,0.0001796882,0.00008358514],"domain_scores_gemma":[0.9977139,0.0005204471,0.001482278,0.0001002698,0.0001537012,0.00002944697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008908208,0.0002121273,0.8959859,0.0008637811,0.0005478318,0.000009296309,0.01644296,0.0004008198,0.004503716,0.0000471727,0.001007946,0.07107026],"study_design_scores_gemma":[0.0004663842,0.001950089,0.9917621,0.0001059935,0.0002290915,0.00006552126,0.004339078,0.0006289508,0.00006232149,0.0003117914,0.00004357693,0.00003510322],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888105,0.002061739,0.002170836,0.006521309,0.0001792346,0.0002446817,0.000003126198,0.000002383941,0.000006148286],"genre_scores_gemma":[0.9968832,0.002641032,0.0002258116,0.00006356193,0.0001738377,0.000002977337,0.00000142792,0.000003554732,0.000004630398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09577622,"threshold_uncertainty_score":0.4398161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3695120793276821,"score_gpt":0.5338763026583545,"score_spread":0.1643642233306724,"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."}}