{"id":"W2269316897","doi":"","title":"USE IN SELECTION OF BLACK CURRANTS OF GENOFOND OF KOKINO BASE STATION OF ALL - RUSSIAN SELECTION AND TECHNOLOGICAL INSTITUTE OF HORTICULTURE AND BREEING NURSERY","year":2013,"lang":"ru","type":"article","venue":"Вестник Орловского государственного аграрного университета","topic":"Berry genetics and cultivation research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Agriculture; Crop; Biology; Horticulture; Resistance (ecology); Plant breeding; Black spot; Biotechnology; Geography; Agricultural science; Agronomy; Ecology; Computer 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":[0.0002673016,0.0004337264,0.0003707109,0.0007947391,0.0009694041,0.0002743605,0.0003362119,0.0002147038,0.00414674],"category_scores_gemma":[0.0001404409,0.0001374482,0.00038096,0.0004356329,0.0001367616,0.0001141139,0.0004242538,0.0002204997,0.001190213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001548893,"about_ca_system_score_gemma":0.000350667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001871987,"about_ca_topic_score_gemma":0.008195972,"domain_scores_codex":[0.9998167,0.00002361831,0.00001168194,0.0000707103,0.0000419186,0.00003540203],"domain_scores_gemma":[0.9998363,0.00001960292,0.00002654942,0.00002450545,0.00002794508,0.00006512347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001003369,0.0003240373,0.07947409,0.0001633899,0.00006929954,0.001146803,0.001319653,0.0001012215,0.8514395,0.0002138833,0.001132022,0.06361271],"study_design_scores_gemma":[0.0001105625,0.002650257,0.8132056,0.00005728456,0.0002414331,0.003379856,0.001766065,0.0002577991,0.1156758,0.00009926082,0.06251022,0.00004579663],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935876,0.0003519615,0.001081008,0.00003783873,0.00002263863,0.0001441352,0.0009572759,0.00002347329,0.003794058],"genre_scores_gemma":[0.9414703,0.001133202,0.01883385,0.0001463688,0.00004902787,0.0004462093,0.008825896,0.0001626404,0.02893246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00414674,"threshold_uncertainty_score":0.01387221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0415560244236737,"score_gpt":0.2631221131943119,"score_spread":0.2215660887706382,"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."}}