{"id":"W6931209717","doi":"10.5281/zenodo.3672418","title":"xieguigang/COVID-19: Map Visualization of the Plague COVID-19 in China","year":2020,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics","funders":"","keywords":"Visualization; Raw data; Data visualization; Table (database); China; Data file","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":[0.0003068773,0.001123388,0.0004550729,0.002403674,0.0005470815,0.001378487,0.0007546562,0.0004480821,0.08427533],"category_scores_gemma":[0.00108897,0.0003865554,0.0008186022,0.003204058,0.0002132026,0.001417685,0.001339085,0.0008453401,0.01676976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006738491,"about_ca_system_score_gemma":0.001660386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05343793,"about_ca_topic_score_gemma":0.06153122,"domain_scores_codex":[0.9997981,0.00002062487,0.000009390455,0.00004183843,0.00007455355,0.00005540012],"domain_scores_gemma":[0.9995546,0.0000616888,0.0000276822,0.00005367252,0.0002128735,0.00008952721],"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":[0.0003437703,0.00007527084,0.01690275,0.001111857,0.0001109198,0.0005911833,0.001717991,0.006787223,0.006425259,0.002442058,0.8800911,0.08340059],"study_design_scores_gemma":[0.0002900845,0.0001102688,0.1217746,0.0006223915,0.0001761452,0.0004789279,0.003058042,0.04145314,0.0140367,0.005617305,0.8120688,0.0003137146],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.07226344,0.0013099,0.04437298,0.003637061,0.001739423,0.0006495827,0.4894074,0.2229937,0.1636265],"genre_scores_gemma":[0.3892693,0.002717391,0.1102575,0.0009958058,0.0004541071,0.0009062688,0.3654137,0.04576922,0.08421677],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.08427533,"threshold_uncertainty_score":0.2819291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02541748795748946,"score_gpt":0.251652718673811,"score_spread":0.2262352307163215,"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."}}