{"id":"W4394493436","doi":"10.6084/m9.figshare.12695772","title":"Additional file 13 of Multi-omics sequencing provides insight into floral transition in Catalpa bungei. C.A. Mey","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Plant Physiology and Cultivation Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Biology; Botany; Computational 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001170337,0.001901544,0.001738964,0.002624108,0.001108848,0.002194211,0.002541598,0.002143112,0.4257722],"category_scores_gemma":[0.005489532,0.0007492051,0.001573207,0.00408753,0.0004038808,0.001762308,0.001512644,0.001424843,0.1275235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187115,"about_ca_system_score_gemma":0.001791028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01047699,"about_ca_topic_score_gemma":0.02193429,"domain_scores_codex":[0.9993942,0.00008022717,0.00007332153,0.0002387191,0.0001074951,0.0001061437],"domain_scores_gemma":[0.9970638,0.001768621,0.0001890557,0.0003088372,0.0004902881,0.0001792858],"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":[0.0002877321,0.00007761771,0.002731805,0.005199046,0.0001340901,0.00009052536,0.00008409421,0.0008804722,0.001211574,0.0007754421,0.9838129,0.004714719],"study_design_scores_gemma":[0.001742026,0.00009963953,0.02108778,0.001592836,0.0002050044,0.0001989818,0.0002130329,0.001143707,0.001766026,0.004345771,0.9674837,0.0001216047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007096138,0.00002007752,0.00005879215,0.00001716295,0.000007580613,0.000008278826,0.9994467,0.0001602003,0.0002102695],"genre_scores_gemma":[0.0008104334,0.00004584417,0.0005598844,0.00007112187,0.000006753457,0.000135796,0.9975935,0.0001723994,0.0006043267],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4257722,"threshold_uncertainty_score":0.8190663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06200842184618435,"score_gpt":0.2319230195256106,"score_spread":0.1699145976794263,"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."}}