{"id":"W6905890044","doi":"10.15468/dl.rc2f5a","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":[0.0009518561,0.002000071,0.001580843,0.004865729,0.001017307,0.002567217,0.002670634,0.001907183,0.1763074],"category_scores_gemma":[0.006253459,0.0009197911,0.001180649,0.009754027,0.0004307252,0.002271048,0.002544416,0.001857542,0.2292544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001501275,"about_ca_system_score_gemma":0.002304314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02104697,"about_ca_topic_score_gemma":0.03338274,"domain_scores_codex":[0.9989711,0.0001398732,0.0001272608,0.0003729311,0.0002180759,0.0001706957],"domain_scores_gemma":[0.9975502,0.0007213136,0.0002286917,0.0006186299,0.0006136273,0.0002675368],"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":[0.00003018612,0.00001072005,0.0003765083,0.0005377291,0.00001375604,0.00001418037,0.00002229008,0.0001217403,0.0001186913,0.0003651626,0.9969136,0.001475436],"study_design_scores_gemma":[0.00006960263,0.000009333356,0.001752627,0.0001852556,0.0000143297,0.00003408457,0.00006581072,0.0001412149,0.0001852259,0.0007930258,0.9967314,0.00001811046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004124675,0.00002588635,0.00004391121,0.00003456861,0.00001209589,0.000005210382,0.9987853,0.000393184,0.0006585507],"genre_scores_gemma":[0.0001616301,0.00003484074,0.0002037152,0.00004832339,0.000003751971,0.00004585357,0.9988083,0.0001721741,0.0005214265],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8236926,"threshold_uncertainty_score":0.5898069,"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."}}