{"id":"W2359673780","doi":"","title":"Breeding and Corresponding Techniques of National Judged Variety Jingke Silage 516","year":2009,"lang":"en","type":"article","venue":"Seed","topic":"Food Quality and Safety Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Silage; Variety (cybernetics); Agronomy; Biology; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0003044577,0.0004355681,0.0002924655,0.0009596276,0.001100328,0.0001988992,0.0003369901,0.00030444,0.002430175],"category_scores_gemma":[0.0002213902,0.0002585242,0.0005916784,0.0003917315,0.0002769098,0.000239243,0.0003472303,0.0007332455,0.0008452845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002430731,"about_ca_system_score_gemma":0.0005122364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002821763,"about_ca_topic_score_gemma":0.007156721,"domain_scores_codex":[0.9997662,0.00003177672,0.00002357881,0.0001048043,0.00004375559,0.00002993728],"domain_scores_gemma":[0.9998201,0.00004223185,0.00001652831,0.00003579876,0.00003503875,0.00005035587],"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":[0.00009887512,0.00007443384,0.001186483,0.00004427277,0.000006178658,0.0001514602,0.000201473,0.00005159689,0.9920421,0.0002075804,0.00006828017,0.005867218],"study_design_scores_gemma":[0.0002105616,0.002399394,0.08435646,0.0000348092,0.0004721668,0.002184692,0.0006596174,0.001756755,0.8839913,0.0004049061,0.0234446,0.0000847306],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9554868,0.0005210701,0.03481815,0.0001124717,0.00008387739,0.0005639549,0.0007313872,0.0002064207,0.007475921],"genre_scores_gemma":[0.8796026,0.001111409,0.0892627,0.0002148065,0.00004532035,0.0006742104,0.004798362,0.0002523123,0.0240383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002821763,"threshold_uncertainty_score":0.008129716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03063144223674618,"score_gpt":0.2540042519696983,"score_spread":0.2233728097329521,"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."}}