{"id":"W6905789950","doi":"10.15468/dl.nfcvh5","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geodetic datum; Coordinate system; Matching (statistics); Download; Range (aeronautics); Geographic coordinate conversion","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":[0.0009118471,0.001810734,0.001501017,0.004777314,0.001018352,0.002887728,0.002704925,0.001789595,0.2027746],"category_scores_gemma":[0.006046322,0.0009101168,0.001353857,0.009760126,0.0004033398,0.002518071,0.002758888,0.001870357,0.2859109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001426061,"about_ca_system_score_gemma":0.002262041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02018616,"about_ca_topic_score_gemma":0.03164713,"domain_scores_codex":[0.9989949,0.0001222412,0.0001284446,0.0003572061,0.0002135302,0.0001836763],"domain_scores_gemma":[0.9976174,0.0006179239,0.0001983367,0.0006657378,0.0006462134,0.0002542631],"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":[0.00002864664,0.000008804803,0.0004164574,0.0005197919,0.00001462208,0.00001595235,0.00002610731,0.0001168622,0.0001239086,0.0003860727,0.9963995,0.001943221],"study_design_scores_gemma":[0.00004796129,0.000006251691,0.001575075,0.0001555458,0.00001199341,0.00003254078,0.00007355548,0.0001432071,0.0001692492,0.0007378326,0.9970317,0.00001517342],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004425574,0.00002962001,0.00006541473,0.00004194331,0.00001664413,0.000005862248,0.9982674,0.0006486084,0.0008801166],"genre_scores_gemma":[0.0001941707,0.00004214377,0.000267533,0.00005472049,0.000004965539,0.00004509834,0.9984841,0.0002566294,0.0006506342],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7972254,"threshold_uncertainty_score":0.6783487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}