{"id":"W58762937","doi":"","title":"Результаты работ по селекции сливы в Южно-Уральском НИИПОК","year":2011,"lang":"ru","type":"article","venue":"Achievements of Science and Technology in Agro-Industrial Complex","topic":"Agricultural Productivity and Crop Improvement","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Agricultural science; Horticulture; Biology","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":[0.0006376551,0.0003490108,0.0003117488,0.001629894,0.001414611,0.002426667,0.0003220795,0.0004752605,0.01205168],"category_scores_gemma":[0.0010043,0.0003652145,0.0002871992,0.001883226,0.0009106732,0.000836372,0.0007505203,0.001220573,0.005781277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193997,"about_ca_system_score_gemma":0.002017536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004308763,"about_ca_topic_score_gemma":0.006524465,"domain_scores_codex":[0.9992433,0.00009250217,0.0000523651,0.0001270204,0.0003862135,0.00009867975],"domain_scores_gemma":[0.9995331,0.000093287,0.0000706568,0.00006451242,0.0001931135,0.00004540314],"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":[0.0001652105,0.00007111837,0.005035274,0.0004951065,0.00003972924,0.00151586,0.001545129,0.001722194,0.05049014,0.1034582,0.008175415,0.8272867],"study_design_scores_gemma":[0.00003124558,0.0002404653,0.01311594,0.0002260327,0.00008618004,0.005146762,0.001312601,0.001687442,0.0627059,0.02907539,0.8862314,0.0001406592],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1893277,0.08881695,0.1491929,0.004509289,0.002714354,0.0003340623,0.001453952,0.001258694,0.5623921],"genre_scores_gemma":[0.7822685,0.03239661,0.0893665,0.0002924273,0.0004605405,0.000264692,0.0005653109,0.0002862852,0.09409924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01205168,"threshold_uncertainty_score":0.04031688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110054695905356,"score_gpt":0.2481903132096805,"score_spread":0.1381356173043245,"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."}}