{"id":"W2354934681","doi":"","title":"Breeding of Early-mature Upland Cotton Xinluzao No.32 and No.33","year":2009,"lang":"en","type":"article","venue":"Seed","topic":"Research in Cotton Cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agronomy; 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":[0.0004001979,0.0003764006,0.0003138779,0.0004451456,0.0006246959,0.0001759916,0.0003533547,0.0001785067,0.001979072],"category_scores_gemma":[0.0001409219,0.0002375857,0.0003246747,0.0002212756,0.0001533888,0.0001860283,0.0002683968,0.000408882,0.0003268325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002911016,"about_ca_system_score_gemma":0.0005012049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003415928,"about_ca_topic_score_gemma":0.01553859,"domain_scores_codex":[0.999891,0.00001404638,0.00000855444,0.00003935541,0.00002216214,0.00002476844],"domain_scores_gemma":[0.9997726,0.00002868671,0.00002501172,0.00002216277,0.00002536562,0.0001261361],"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":[0.0003200567,0.0002108657,0.005958114,0.00006264931,0.00001350919,0.0004968295,0.0004367792,0.0001308255,0.9784385,0.0003592829,0.0001986826,0.01337393],"study_design_scores_gemma":[0.0004003432,0.005257212,0.6537368,0.00008066706,0.0002820927,0.00343846,0.00159745,0.003671923,0.2909359,0.0005112572,0.03996287,0.0001249201],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966964,0.00008064581,0.001132863,0.00003003174,0.00001247295,0.00009802121,0.0001675579,0.00002172164,0.001760366],"genre_scores_gemma":[0.9743193,0.000209341,0.009001884,0.00005927126,0.00001061784,0.000174006,0.001119617,0.00004191821,0.01506401],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003415928,"threshold_uncertainty_score":0.006792128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421945949370374,"score_gpt":0.2531722135829307,"score_spread":0.228952754089227,"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."}}