{"id":"W3027205249","doi":"10.36461/np.2020.54.1.006","title":"ОЦЕНКА СОРТООБРАЗЦОВ КРАМБЕ В ЗАВИСИМОСТИ ОТ ГИДРОТЕРМАЛЬНЫХ УСЛОВИЙ","year":2020,"lang":"ru","type":"article","venue":"Niva Povolzh`ia","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Adaptability; Productivity; Yield (engineering); Research Object; Animal science; Agronomy; Mathematics; Biology; Horticulture; Geography; Ecology; Physics","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":[0.002964034,0.0006819389,0.0004422895,0.002169905,0.004007,0.01057066,0.001032943,0.002215367,0.03848059],"category_scores_gemma":[0.00614994,0.0006090094,0.0008322202,0.002312653,0.004569908,0.004737252,0.003574474,0.003419479,0.01804877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004729808,"about_ca_system_score_gemma":0.009022018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0108013,"about_ca_topic_score_gemma":0.01299442,"domain_scores_codex":[0.9957147,0.001098655,0.0002414396,0.0006920335,0.001740693,0.0005124397],"domain_scores_gemma":[0.9966694,0.0007496218,0.0003609681,0.0005566069,0.001213469,0.0004500661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00008147561,0.0000647278,0.002859849,0.0004257531,0.0000404594,0.0004816121,0.005333071,0.0007920249,0.002116981,0.8382634,0.0349875,0.1145531],"study_design_scores_gemma":[0.00001824466,0.00003372775,0.003558667,0.0003303982,0.00003517341,0.00041967,0.00269398,0.0005285275,0.00180063,0.09530716,0.895207,0.00006672036],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02516224,0.01083092,0.04823358,0.01684976,0.002075336,0.0002361329,0.0008828957,0.0006629044,0.8950662],"genre_scores_gemma":[0.5784736,0.01722887,0.06039815,0.003570289,0.001482527,0.0006191161,0.001380467,0.001040437,0.3358066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03848059,"threshold_uncertainty_score":0.1287304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03351290385786151,"score_gpt":0.2356329983930685,"score_spread":0.202120094535207,"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."}}