{"id":"W7055474400","doi":"","title":"CLIM4OMICS: a geospatially comprehensive climate and\\nmulti-OMICS database for maize phenotype predictability\\nin the United States and Canada","year":2023,"lang":"en","type":"article","venue":"Lincoln (University of Nebraska)","topic":"Particle accelerators and beam dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metadata; Environmental data; Big data; Analytics; Data quality; Field (mathematics); Pipeline (software); Consistency (knowledge bases); Raw data","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009955619,0.001173178,0.0007376092,0.004627616,0.001730454,0.002679872,0.002288998,0.0007500527,0.006423819],"category_scores_gemma":[0.003483355,0.0005811523,0.0008167081,0.008373225,0.0004819168,0.001516155,0.002133927,0.0009238273,0.003922091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007583802,"about_ca_system_score_gemma":0.02054144,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7785367,"about_ca_topic_score_gemma":0.8106778,"domain_scores_codex":[0.9992218,0.00004105176,0.00006619232,0.000210069,0.0003353976,0.0001254185],"domain_scores_gemma":[0.9973161,0.0001830268,0.000231632,0.0004249614,0.001426218,0.0004181462],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001063502,0.0001408368,0.0527166,0.001521423,0.0005609,0.0006255949,0.001012909,0.01441428,0.02273283,0.02141142,0.7744714,0.1093283],"study_design_scores_gemma":[0.000184456,0.0000332719,0.09351314,0.0003300519,0.0001706408,0.000154898,0.0007663844,0.0193192,0.009381466,0.006052065,0.8698145,0.0002799666],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01084474,0.0005091564,0.008500047,0.0002693205,0.00004157368,0.0001638096,0.9608636,0.01086682,0.007940839],"genre_scores_gemma":[0.02544887,0.0006423476,0.01730781,0.0001513243,0.00001178048,0.0001887276,0.9531881,0.0008955,0.002165461],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2214633,"threshold_uncertainty_score":0.445535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299514525542069,"score_gpt":0.1967143406081526,"score_spread":0.1837191953527319,"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."}}