{"id":"W4226392870","doi":"10.1002/essoar.10508840.3","title":"How we built it: a community network connecting phenomics developers with plant scientists","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Phenomics; World Wide Web; Computer science; Data science; Knowledge management; Biology","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":[0.007602843,0.0006582148,0.0002270395,0.001691882,0.005712821,0.005900624,0.001341712,0.002579131,0.01655079],"category_scores_gemma":[0.02139289,0.0005417768,0.0005181165,0.001268177,0.002662393,0.01414493,0.009932567,0.003608367,0.00722185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443218,"about_ca_system_score_gemma":0.004981847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003370665,"about_ca_topic_score_gemma":0.00525174,"domain_scores_codex":[0.9957592,0.002120113,0.0001021874,0.0005252879,0.0009930136,0.000500307],"domain_scores_gemma":[0.9824859,0.002976517,0.0006419364,0.002244268,0.002956291,0.00869514],"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":[0.0002253963,0.0003987067,0.007431162,0.0003585383,0.00005735348,0.001799532,0.01939173,0.001419037,0.008641367,0.05860872,0.5480825,0.3535859],"study_design_scores_gemma":[0.00002898095,0.0000836034,0.00125422,0.0001725279,0.00001709754,0.000314553,0.004656177,0.00121766,0.00122845,0.01674443,0.9742188,0.0000634524],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1050903,0.005055221,0.3222971,0.2366728,0.01602397,0.001380887,0.002401611,0.01651313,0.294565],"genre_scores_gemma":[0.3800832,0.004558041,0.3292575,0.02741787,0.00292874,0.001685565,0.006007698,0.01008367,0.2379777],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01655079,"threshold_uncertainty_score":0.05536795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05037405253445733,"score_gpt":0.2953026422375424,"score_spread":0.2449285897030851,"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."}}