{"id":"W2952704823","doi":"","title":"МОЛОЧНАЯ ПРОДУКТИВНОСТЬ ЧЕРНО-ПЕСТРЫХ КОРОВ PАЗЛИЧНОЙ СЕЛЕКЦИИ","year":2016,"lang":"ru","type":"article","venue":"Doklady of the National Academy of Sciences of Belarus","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Selection (genetic algorithm); Milk production; Agricultural science; Economics; Animal science; 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":[0.0006122992,0.0003075213,0.0003148228,0.001764779,0.0009132434,0.002212467,0.0002801426,0.0004024185,0.009991595],"category_scores_gemma":[0.001276718,0.0003850113,0.0003597401,0.00162922,0.001639624,0.0007918171,0.0006797195,0.0008384594,0.002949557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008678289,"about_ca_system_score_gemma":0.001315566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003259602,"about_ca_topic_score_gemma":0.004965816,"domain_scores_codex":[0.9993401,0.0001208515,0.00003360592,0.0001265263,0.0002956482,0.00008317547],"domain_scores_gemma":[0.9994565,0.0001619872,0.0001241027,0.00008412871,0.0001345707,0.00003880855],"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":[0.0002170089,0.000143293,0.01245349,0.0007913886,0.0001131249,0.001804602,0.004139586,0.004555519,0.08030872,0.3603715,0.005900002,0.5292017],"study_design_scores_gemma":[0.00009593587,0.0005215473,0.06833606,0.0005009046,0.0002674038,0.006173257,0.004676534,0.005807801,0.06023129,0.2534536,0.5996431,0.0002925325],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3486102,0.04187828,0.2209002,0.004479488,0.001004151,0.0002309771,0.00117133,0.0004915996,0.3812338],"genre_scores_gemma":[0.8953654,0.01332532,0.06189567,0.0001287153,0.0002407877,0.0002029515,0.0002182886,0.0001035071,0.02851926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009991595,"threshold_uncertainty_score":0.03342521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08008694617853919,"score_gpt":0.3521353650656918,"score_spread":0.2720484188871526,"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."}}