{"id":"W6943264263","doi":"10.15468/dl.k9nsc3","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Alien; Range (aeronautics); State (computer science)","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":[0.0008623468,0.001946506,0.001529574,0.004809107,0.0009334903,0.002436734,0.002523253,0.001857311,0.1584082],"category_scores_gemma":[0.005917023,0.0008378796,0.001133222,0.00968683,0.0004091587,0.002145492,0.002395747,0.001722842,0.2169055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001435545,"about_ca_system_score_gemma":0.002132291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02013622,"about_ca_topic_score_gemma":0.03256692,"domain_scores_codex":[0.9990188,0.0001329915,0.0001256583,0.0003504084,0.0002078991,0.0001642022],"domain_scores_gemma":[0.9976726,0.0006733143,0.0002293438,0.000581411,0.0005919329,0.0002513684],"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":[0.00003203969,0.00001089179,0.0004161436,0.0005435744,0.00001408406,0.00001497396,0.00002129418,0.0001297147,0.0001177834,0.0003523156,0.9968136,0.001533714],"study_design_scores_gemma":[0.00007213488,0.00001007966,0.001970654,0.000190416,0.00001480889,0.00003715193,0.00006695242,0.0001610301,0.0001910359,0.0007705078,0.9964969,0.00001831921],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004571464,0.00002695436,0.00004018977,0.00003351796,0.00001155089,0.000004943584,0.9988436,0.0003716569,0.0006217727],"genre_scores_gemma":[0.0001735694,0.00003502703,0.0001897672,0.0000453568,0.000003839718,0.00004217233,0.9988662,0.0001476242,0.0004963859],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8415918,"threshold_uncertainty_score":0.5299281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}