{"id":"W14074995","doi":"","title":"水稻窄叶突变体nal7（t）的遗传分析与基因定位","year":2010,"lang":"zh","type":"article","venue":"分子植物育种","topic":"Plant Molecular Biology Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":[0.0003968785,0.0003583716,0.0002992815,0.0004628468,0.0009665255,0.001676133,0.0004438364,0.0007728825,0.009129536],"category_scores_gemma":[0.0005624329,0.0002599497,0.0005986867,0.0004063943,0.0009408286,0.00110124,0.0004100408,0.0009155083,0.003935695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001789786,"about_ca_system_score_gemma":0.001180307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003643705,"about_ca_topic_score_gemma":0.004575716,"domain_scores_codex":[0.9996425,0.00006140403,0.00002027773,0.00009653899,0.0001044008,0.00007488889],"domain_scores_gemma":[0.9995881,0.00009794802,0.00004203322,0.00003150629,0.0001855341,0.00005494575],"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":[0.0009101346,0.0001181217,0.007048113,0.0005654243,0.0001007719,0.0006405499,0.0009614679,0.002434008,0.9125096,0.01368523,0.00319053,0.05783612],"study_design_scores_gemma":[0.00009932787,0.0006491262,0.02874053,0.00009913122,0.0001985912,0.00128225,0.003495811,0.004936628,0.8557791,0.01142901,0.09316106,0.0001294262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8546641,0.00516585,0.03312721,0.001881927,0.0004078793,0.0001986401,0.001892166,0.0004775398,0.1021847],"genre_scores_gemma":[0.939499,0.001628473,0.01503781,0.0004241124,0.00005352256,0.0001409985,0.002654511,0.00012716,0.04043451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009129536,"threshold_uncertainty_score":0.0305413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02370685265815258,"score_gpt":0.2618536403641643,"score_spread":0.2381467877060117,"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."}}