{"id":"W2803315948","doi":"10.3390/agronomy8050078","title":"Challenges in Using Precision Agriculture to Optimize Symbiotic Nitrogen Fixation in Legumes: Progress, Limitations, and Future Improvements Needed in Diagnostic Testing","year":2018,"lang":"en","type":"article","venue":"Agronomy","topic":"Legume Nitrogen Fixing Symbiosis","field":"Agricultural and Biological Sciences","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Global Affairs Canada; International Development Research Centre","keywords":"Nitrogen fixation; Precision agriculture; Agriculture; Nitrogen; Biotechnology; Agronomy; Agricultural engineering; Biology; Computer science; Environmental science; Engineering; Chemistry; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000333786,0.0001921501,0.0002105093,0.00007615175,0.00009679212,0.00008454482,0.0001711461,0.0001482829,0.00001413598],"category_scores_gemma":[0.0004669136,0.0000930729,0.00002723821,0.0007940896,0.00004331395,0.000326294,0.0001087113,0.0001387155,0.00001191965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001343135,"about_ca_system_score_gemma":0.0000141218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007712936,"about_ca_topic_score_gemma":0.004124764,"domain_scores_codex":[0.9985473,0.0001161272,0.0003678065,0.0004654314,0.0001486417,0.0003547374],"domain_scores_gemma":[0.9990414,0.0006090541,0.0001154516,0.00006766814,0.00008319185,0.00008322316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000354076,0.0003364847,0.6064623,0.00002660346,0.00001375648,0.00001086059,0.002223519,0.00001761505,0.05247147,0.00005687034,0.00008250885,0.3382626],"study_design_scores_gemma":[0.0005495719,0.0003014386,0.9868383,0.0003506128,0.00001275321,0.000006130437,0.004347441,0.0002149273,0.006299555,0.0004770628,0.0002731202,0.0003290474],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950544,0.001590449,6.51671e-7,0.002185323,0.00007750562,0.0008486658,0.00000442656,0.00002811439,0.0002104312],"genre_scores_gemma":[0.9947848,0.00008613276,0.004597654,0.0001031878,0.0002981146,0.00009635325,0.000024835,0.000002436948,0.000006510988],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.380376,"threshold_uncertainty_score":0.3795403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05487955861661417,"score_gpt":0.2499468494997438,"score_spread":0.1950672908831297,"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."}}