{"id":"W2369197500","doi":"","title":"Thinking on Increasing Seed Management Ability of Fujian Provinc","year":2011,"lang":"en","type":"article","venue":"Seed","topic":"Logistics and Infrastructure Analysis","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Business; Chemistry; Horticulture; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003047264,0.00008075051,0.0001301256,0.00001176243,0.00009255569,0.00001802502,0.0002083787,0.00004296561,0.0001965329],"category_scores_gemma":[0.00002956733,0.00002772578,0.00007440072,0.0001769325,0.00004804901,0.00003754854,0.00007134164,0.00005578536,0.00001021488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001726158,"about_ca_system_score_gemma":0.000002227749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001117706,"about_ca_topic_score_gemma":0.0001577882,"domain_scores_codex":[0.9993059,0.00004993091,0.0001635569,0.0001763651,0.0001690524,0.0001351708],"domain_scores_gemma":[0.9997227,0.00004175639,0.00008579727,0.00007140969,0.00003867747,0.00003965247],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002823846,0.0003494995,0.6729773,0.00005945802,0.0002009575,0.00001467725,0.0009003928,0.00001488172,0.2358014,0.03656418,0.000068603,0.05276633],"study_design_scores_gemma":[0.00005111763,0.0001235244,0.9854093,0.0000111094,0.00002770083,4.449447e-7,0.0002135745,0.0000428872,0.002465129,0.01133539,0.000247125,0.0000726862],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9504624,0.000008423805,0.00001367495,0.0001085773,0.00004289755,0.0001028686,0.000007358098,0.0000267121,0.0492271],"genre_scores_gemma":[0.9987833,0.00000429716,0.0009253949,0.0001609865,0.00004899629,0.000002046721,0.00001340285,4.612593e-7,0.00006109672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.312432,"threshold_uncertainty_score":0.2151897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964210971085802,"score_gpt":0.1982481254884349,"score_spread":0.1786060157775768,"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."}}