{"id":"W4384133453","doi":"10.1101/2023.07.12.548745","title":"Cotton Microbiome Profiling and Cotton Leaf Curl Disease (CLCuD) Suppression through Microbial Consortia associated with <i>Gossypium arboreum</i>","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Plant-Microbe Interactions and Immunity","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Pakistan Academy of Sciences; Higher Education Commission, Pakistan; University of Glasgow; UK Research and Innovation; Natural Environment Research Council; Alberta Agricultural Research Institute; Sight Research UK; Alexander von Humboldt-Stiftung","keywords":"Biology; Gossypium; Microbiome; Rhizosphere; Phyllosphere; Botany; Genetics; Bacteria","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001799134,0.0003021916,0.000241464,0.000392506,0.0003026602,0.0004322421,0.00008463193,0.000215756,0.0007639974],"category_scores_gemma":[0.0001794446,0.00009413799,0.0001757419,0.0003330993,0.0001662622,0.0001743494,0.0004000633,0.0002276929,0.000172052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621333,"about_ca_system_score_gemma":0.0002399231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003263887,"about_ca_topic_score_gemma":0.003836075,"domain_scores_codex":[0.9998517,0.00001716368,0.000006714846,0.00005347922,0.00002894699,0.00004198544],"domain_scores_gemma":[0.9998894,0.00001105145,0.00004288004,0.000006701849,0.0000173436,0.00003260325],"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":[0.0001953382,0.00002934297,0.02170967,0.00006626901,0.0000172991,0.00008154487,0.0001518488,0.0000541467,0.9746101,0.00003001121,0.00008043635,0.002973886],"study_design_scores_gemma":[0.0000139098,0.0005837439,0.8839339,0.00003644071,0.00005822044,0.0004786338,0.001059278,0.0009574356,0.1096952,0.0001136628,0.003049906,0.00001968163],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979165,0.0002590507,0.0003132033,0.00004824205,0.000006251447,0.00001306435,0.0009502,0.00001814975,0.0004752038],"genre_scores_gemma":[0.9963866,0.0002327499,0.0008033491,0.00006858161,0.000007043636,0.00002433386,0.001580689,0.00001016701,0.0008866031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003263887,"threshold_uncertainty_score":0.006489813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212441154243719,"score_gpt":0.2168303972036431,"score_spread":0.1947059856612059,"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."}}