{"id":"W3040855850","doi":"","title":"ИСХОДНЫЙ МАТЕРИАЛ ДЛЯ СЕЛЕКЦИИ СОРТОВ ЯРОВОЙ МЯГКОЙ ПШЕНИЦЫ В УСЛОВИЯХ КИРОВСКОЙ ОБЛАСТИ","year":2016,"lang":"ru","type":"article","venue":"Вестник НГАУ (Новосибирский государственный аграрный университет)","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ripening; Productivity; Crop; Agronomy; Cultivar; Grain quality; Biomass (ecology); Horticulture; Resistance (ecology); Biology; High protein; Yield (engineering); Geography; Food science","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":[0.0005245281,0.0002419212,0.0002446066,0.001629377,0.0009946029,0.001895944,0.0003297975,0.000552683,0.009954467],"category_scores_gemma":[0.001086016,0.0003925232,0.0002764751,0.001568705,0.001099307,0.0008261387,0.0006632066,0.0007237683,0.00281654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007670453,"about_ca_system_score_gemma":0.001067701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002716032,"about_ca_topic_score_gemma":0.004394078,"domain_scores_codex":[0.999402,0.00008420576,0.00002826326,0.0001157869,0.0002922367,0.00007753863],"domain_scores_gemma":[0.9994554,0.0001385586,0.0001147044,0.00007589921,0.0001630304,0.00005244815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003712916,0.0001395095,0.01318937,0.0006899544,0.0000698483,0.002328584,0.003165989,0.00289365,0.27791,0.1092005,0.005577416,0.5844639],"study_design_scores_gemma":[0.00009963565,0.0006643742,0.04872657,0.0003329967,0.0002511918,0.006101834,0.004262479,0.006725259,0.2241604,0.05396588,0.6544163,0.000293133],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5340309,0.04157299,0.1448317,0.002788116,0.001440818,0.0002478801,0.0009544445,0.0004882426,0.2736449],"genre_scores_gemma":[0.915429,0.009756773,0.03934196,0.0001118623,0.0002034502,0.0001509434,0.0002071309,0.000123365,0.03467549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009954467,"threshold_uncertainty_score":0.03330106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801685566868975,"score_gpt":0.193137495665475,"score_spread":0.1751206399967853,"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."}}