{"id":"W6962085421","doi":"10.15468/dl.9bbnth","title":"Occurrence Download","year":2024,"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); Range (aeronautics); Data set; 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":[0.0007881089,0.002191757,0.00181362,0.005482789,0.001153994,0.003369062,0.002886531,0.002018203,0.2150992],"category_scores_gemma":[0.006431606,0.0009304725,0.001572527,0.009583932,0.0003727043,0.003306011,0.003244928,0.001961799,0.3226888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527781,"about_ca_system_score_gemma":0.002310962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01931312,"about_ca_topic_score_gemma":0.03290738,"domain_scores_codex":[0.9987852,0.0001327432,0.0001608639,0.0004448732,0.0002740302,0.0002022031],"domain_scores_gemma":[0.9975315,0.0005867186,0.0002045693,0.000686725,0.0007032496,0.0002872261],"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":[0.00004267056,0.00001290287,0.0004459319,0.0005706416,0.00001411671,0.00002153591,0.00002465535,0.0001006645,0.0001045982,0.0003670269,0.9953112,0.00298409],"study_design_scores_gemma":[0.00005153863,0.00001119683,0.001459947,0.0001655967,0.00001318285,0.00004871345,0.00007819811,0.0002269385,0.0001724364,0.0007148446,0.99704,0.00001752066],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007754984,0.00006047749,0.0001085515,0.00006965544,0.00002917984,0.000009208195,0.9966605,0.001623397,0.001361545],"genre_scores_gemma":[0.0002535123,0.0000685685,0.0004077919,0.00007920264,0.000008207783,0.00004669276,0.9976584,0.0004237147,0.001053881],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7849008,"threshold_uncertainty_score":0.7195784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}