{"id":"W2122377450","doi":"10.1637/7968-031907-regr.1","title":"Prediction of Optimal Vaccination Timing for Infectious Bursal Disease Based on Chick Weight","year":2007,"lang":"en","type":"article","venue":"Avian Diseases","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de La Pocatiere; Université de Montréal","funders":"","keywords":"Infectious bursal disease; Biology; Broiler; Vaccination; Antibody; Weight gain; Antibody titer; Virus; Titer; Animal science; Veterinary medicine; Growth rate; Body weight; Physiology; Virology; Immunology; Endocrinology; Medicine; Virulence","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":[],"consensus_categories":[],"category_scores_codex":[0.00005400684,0.00008245504,0.00009245155,0.00002025619,0.0001162787,0.000008927101,0.00006348809,0.00004210146,0.0002123609],"category_scores_gemma":[0.00006807823,0.0000380584,0.0001098994,0.0001181334,0.00002405068,0.00006498177,0.000008922581,0.00003574518,0.000005871743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001836377,"about_ca_system_score_gemma":0.000007871247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001285378,"about_ca_topic_score_gemma":0.00001323232,"domain_scores_codex":[0.9994031,0.0000248059,0.0001385753,0.0001685137,0.0000998123,0.0001652406],"domain_scores_gemma":[0.9994874,0.0002159071,0.00006673714,0.00003404788,0.00006413719,0.0001317892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007398805,0.004454184,0.6890221,0.00023581,0.00006291465,0.00001208539,0.00006301011,0.0008239089,0.1212261,0.006618288,0.005174199,0.1649086],"study_design_scores_gemma":[0.0003617243,0.0006580626,0.9947115,0.00002022729,0.0000289945,2.124643e-7,0.00002303871,0.001695649,0.00043494,0.0006731745,0.001317664,0.0000747795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979159,0.00006942226,0.0004162139,0.0003464188,0.0001010316,0.0002657129,0.0005560906,0.00007015542,0.0002591106],"genre_scores_gemma":[0.9987224,0.000008087641,0.00004320322,0.0002986038,0.0003255462,0.00002175441,0.0005454134,0.000001086837,0.00003392204],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3056894,"threshold_uncertainty_score":0.2325203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02125133703715218,"score_gpt":0.2396555957043371,"score_spread":0.218404258667185,"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."}}