{"id":"W6906110730","doi":"10.15468/dl.p75etu","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":[0.0009190956,0.001977732,0.001508452,0.004912911,0.0009729689,0.002468826,0.002636264,0.001909557,0.1699441],"category_scores_gemma":[0.005927719,0.0008940336,0.001183175,0.009932409,0.0004445933,0.002195405,0.00248548,0.001783526,0.2285232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001464071,"about_ca_system_score_gemma":0.002254297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02057436,"about_ca_topic_score_gemma":0.03316971,"domain_scores_codex":[0.9989744,0.0001397001,0.0001305558,0.0003706136,0.0002105917,0.0001742531],"domain_scores_gemma":[0.9975945,0.000687187,0.0002304452,0.0006054736,0.0006083224,0.0002740753],"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":[0.00003042646,0.00001118927,0.0003995827,0.0005065346,0.00001313163,0.00001335111,0.00002036104,0.0001235899,0.0001100844,0.0003323918,0.9969958,0.001443514],"study_design_scores_gemma":[0.00007722279,0.00001045469,0.001927935,0.0001892494,0.00001464276,0.00003515894,0.0000705013,0.0001516728,0.0001822847,0.0007712175,0.9965518,0.00001787666],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004477512,0.00002542106,0.00003749991,0.00003312378,0.00001229784,0.000004884006,0.9988781,0.0003376779,0.0006261459],"genre_scores_gemma":[0.0001619395,0.00003276168,0.0001815677,0.00004576959,0.000003758075,0.0000404716,0.9989089,0.0001384852,0.0004863364],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8300558,"threshold_uncertainty_score":0.5685198,"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."}}