{"id":"W6906186279","doi":"10.15468/dl.ugqekg","title":"Occurrence Download","year":2017,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); R package; Range (aeronautics); Polygon (computer graphics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008734846,0.001937284,0.00151727,0.005339456,0.0009799718,0.002965498,0.002789664,0.001977751,0.1940357],"category_scores_gemma":[0.006564141,0.0009165446,0.001219665,0.01169764,0.0004058335,0.002676685,0.002771329,0.00206278,0.2665154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001647459,"about_ca_system_score_gemma":0.002340843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02218169,"about_ca_topic_score_gemma":0.03745228,"domain_scores_codex":[0.9989498,0.0001394529,0.0001374262,0.0003687884,0.0002305201,0.0001739732],"domain_scores_gemma":[0.9975234,0.0006863592,0.000219364,0.00062235,0.0006842489,0.0002642978],"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":[0.00002327932,0.000008618009,0.0003606833,0.0004791145,0.00001324055,0.0000137987,0.00002346535,0.000111221,0.00007836336,0.000387372,0.9969291,0.001571744],"study_design_scores_gemma":[0.00005238618,0.000005929346,0.001372875,0.0001840766,0.00001191949,0.00003329516,0.00007724984,0.000138131,0.0001354127,0.0007963201,0.9971775,0.00001495433],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003899507,0.00003117202,0.00005353182,0.00004089077,0.00001328676,0.000004812349,0.9985576,0.0004450477,0.0008145283],"genre_scores_gemma":[0.0001731614,0.00004294143,0.0002329546,0.00004890353,0.000004087818,0.00004020178,0.9986488,0.0001970241,0.0006119439],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8059642,"threshold_uncertainty_score":0.6491143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387106755018206,"score_gpt":0.2528130017232275,"score_spread":0.2289419341730454,"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."}}