{"id":"W4200022944","doi":"10.1002/essoar.10508840.2","title":"How we built it: a community network connecting phenomics developers with plant scientists","year":2021,"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; Data science; Computer science; 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007629613,0.000659138,0.0002273146,0.001685678,0.005649575,0.005870621,0.001339347,0.002577151,0.01650415],"category_scores_gemma":[0.02140148,0.0005429736,0.0005192452,0.001267042,0.002649216,0.01415219,0.009896363,0.003572432,0.007255325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001430604,"about_ca_system_score_gemma":0.004921775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003367586,"about_ca_topic_score_gemma":0.005243774,"domain_scores_codex":[0.9957567,0.002122536,0.0001022757,0.0005227457,0.000996345,0.000499298],"domain_scores_gemma":[0.9827361,0.002964464,0.0006347928,0.002224877,0.002916564,0.008523058],"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":[0.0002253031,0.0003946774,0.007361824,0.0003590768,0.00005708719,0.001784899,0.01914756,0.001427177,0.008589851,0.05915266,0.5472783,0.3542216],"study_design_scores_gemma":[0.00002881684,0.00008238872,0.001249416,0.0001727218,0.00001701836,0.0003125535,0.004597481,0.001212978,0.001226746,0.01685749,0.9741793,0.00006307985],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.103883,0.005050678,0.3252745,0.2351369,0.01597054,0.001367634,0.002402473,0.01658807,0.2943262],"genre_scores_gemma":[0.3771357,0.004608539,0.3320877,0.02693824,0.002933325,0.001673763,0.006070475,0.01018298,0.2383693],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9941294,"threshold_uncertainty_score":0.05521184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0480781596008065,"score_gpt":0.289339658671768,"score_spread":0.2412614990709615,"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."}}