{"id":"W2384503378","doi":"","title":"Application of Similarity-difference Analysis Method on Regional Test of Soybean","year":2007,"lang":"en","type":"article","venue":"Seed","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Similarity (geometry); Mathematics; Biological system; Computer science; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001224115,0.0004278553,0.0006757202,0.002000805,0.0004955114,0.0005330688,0.0008611714,0.0005561066,0.00140538],"category_scores_gemma":[0.00327901,0.0001657597,0.0008020209,0.001212978,0.00036463,0.0006812597,0.0006064617,0.0003597324,0.0002722242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000441514,"about_ca_system_score_gemma":0.0009227542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003997862,"about_ca_topic_score_gemma":0.003075727,"domain_scores_codex":[0.9990871,0.0002132347,0.00005544922,0.0002745489,0.0002977817,0.000071905],"domain_scores_gemma":[0.9982373,0.000728147,0.00009863777,0.0001459408,0.0006818928,0.0001080752],"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":[0.00122793,0.0003654096,0.04687585,0.0002789519,0.0002326575,0.000457033,0.0003661833,0.07588222,0.1846312,0.008853658,0.002134811,0.6786941],"study_design_scores_gemma":[0.0000640443,0.0002972887,0.03008063,0.000007556111,0.0001194393,0.0004433701,0.0001742903,0.9072988,0.05571271,0.004026753,0.001730081,0.00004497381],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3272472,0.0003040227,0.6688111,0.00009471479,0.0000803008,0.00006770439,0.0001896334,0.0006917482,0.002513666],"genre_scores_gemma":[0.819075,0.00007454305,0.1791144,0.00002600162,0.00002735807,0.00004512219,0.00038812,0.00006278196,0.001186695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003997862,"threshold_uncertainty_score":0.007949173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347268435017499,"score_gpt":0.2842749862079463,"score_spread":0.2708023018577713,"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."}}