{"id":"W2941288780","doi":"10.1002/pld3.133","title":"Directions for research and training in plant omics: Big Questions and Big Data","year":2019,"lang":"en","type":"article","venue":"Plant Direct","topic":"Photosynthetic Processes and Mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Science Foundation","keywords":"Arabidopsis; Arabidopsis thaliana; Training (meteorology); Big data; Graduate students; Engineering ethics; Data science; Biology; Computer science; Medical education; Engineering; Medicine; Geography; Genetics; Data mining","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":[0.1358357,0.001384618,0.002343122,0.00334387,0.004735005,0.01885236,0.006762279,0.01517696,0.0129668],"category_scores_gemma":[0.09310728,0.001318014,0.002709937,0.004182524,0.01309402,0.0316133,0.01413237,0.03141218,0.003972007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008032865,"about_ca_system_score_gemma":0.03217033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004706598,"about_ca_topic_score_gemma":0.00606193,"domain_scores_codex":[0.9694958,0.0197516,0.001353735,0.002081434,0.005237558,0.002079922],"domain_scores_gemma":[0.7232172,0.1975083,0.006570517,0.01460786,0.02571842,0.03237769],"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":[0.0003090055,0.0003788757,0.003212827,0.003797497,0.0001933605,0.0003136835,0.003529548,0.002672756,0.002755987,0.1730728,0.634763,0.1750006],"study_design_scores_gemma":[0.0001107877,0.0001365111,0.002671195,0.003896794,0.0000606398,0.0002492675,0.008980758,0.004330364,0.001023329,0.4952139,0.4831291,0.0001973415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00218978,0.03246981,0.01812904,0.9375466,0.006496449,0.00009631603,0.0005951734,0.0002633424,0.002213557],"genre_scores_gemma":[0.09623411,0.1476821,0.2639007,0.4359371,0.04042285,0.001976352,0.005105382,0.0008939219,0.007847466],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1358357,"threshold_uncertainty_score":0.7183763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.124075684394851,"score_gpt":0.3350276905840622,"score_spread":0.2109520061892112,"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."}}