{"id":"W4286610718","doi":"10.1186/s12864-022-08768-2","title":"Proteomics data analysis using multiple statistical approaches identified proteins and metabolic networks associated with sucrose accumulation in sugarcane","year":2022,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Sugarcane Cultivation and Processing","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture","funders":"Science and Technology Major Project of Guangxi; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Proteomics; Biology; Computational biology; Statistical analysis; DNA microarray; Bioinformatics; Biotechnology; Genetics; Gene; Gene expression; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001449191,0.0009895439,0.000874724,0.003258307,0.0008931282,0.001249833,0.0005622979,0.0005247344,0.0009054099],"category_scores_gemma":[0.001730924,0.0002108308,0.001986204,0.004057822,0.0003326201,0.0005742104,0.0006586654,0.0006013899,0.0004141364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007491437,"about_ca_system_score_gemma":0.001249456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004106426,"about_ca_topic_score_gemma":0.004944904,"domain_scores_codex":[0.9992408,0.00008151893,0.00007667188,0.0003161203,0.0001771574,0.0001078314],"domain_scores_gemma":[0.9993019,0.000230907,0.0001561265,0.0000593741,0.0002012718,0.00005031791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002611265,0.0007734377,0.3890215,0.002630045,0.003828909,0.001456403,0.0005652237,0.03866953,0.325169,0.001465757,0.007388948,0.22642],"study_design_scores_gemma":[0.00005045222,0.0004584946,0.6412616,0.0001017583,0.001264222,0.0008986079,0.000611485,0.285354,0.05768827,0.00402189,0.008125181,0.0001640296],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9203355,0.002314433,0.05337626,0.0004257114,0.00006701804,0.0001917953,0.02029216,0.001744609,0.001252523],"genre_scores_gemma":[0.9137972,0.0009125717,0.05843086,0.0001226021,0.00004364883,0.0003595319,0.02529964,0.0001382998,0.0008956872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004106426,"threshold_uncertainty_score":0.008165061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.223878911594601,"score_gpt":0.291588319271855,"score_spread":0.06770940767725392,"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."}}