{"id":"W104670047","doi":"","title":"Биохимический профиль крови импортного скота на различных этапах адаптации, возраста и физиологического состояния","year":2013,"lang":"ru","type":"article","venue":"Известия Оренбургского государственного аграрного университета","topic":"Animal Nutrition and Health","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Biology; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002785709,0.0001493261,0.0001042894,0.0006870342,0.0008863309,0.001043567,0.0002199976,0.0002666253,0.003557046],"category_scores_gemma":[0.0005166127,0.0001746304,0.0001547269,0.0007510658,0.001007465,0.0002945982,0.0002837768,0.0003679161,0.0004577983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001324157,"about_ca_system_score_gemma":0.003285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07128618,"about_ca_topic_score_gemma":0.1270268,"domain_scores_codex":[0.9997135,0.00003238693,0.00001026914,0.0000459433,0.0001376237,0.00006024372],"domain_scores_gemma":[0.9997039,0.00005864537,0.00005968866,0.00002379192,0.0001069438,0.00004696495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007683581,0.0001746125,0.06894495,0.0003786501,0.00008292516,0.002189264,0.008598595,0.002167982,0.3843161,0.1059344,0.00222746,0.4242167],"study_design_scores_gemma":[0.0001058348,0.0005627468,0.5588489,0.0001769035,0.0002676178,0.004884965,0.01051895,0.004347667,0.1470196,0.03320457,0.2398318,0.0002304532],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9142534,0.00425327,0.01488898,0.0006498392,0.00008025236,0.00005682609,0.0003806576,0.00007405966,0.06536284],"genre_scores_gemma":[0.9816602,0.001106368,0.008627515,0.00002512646,0.00001853905,0.00001925798,0.0001020531,0.00001500336,0.008425911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07128618,"threshold_uncertainty_score":0.1417425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03412161012023957,"score_gpt":0.2390418813873091,"score_spread":0.2049202712670695,"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."}}