{"id":"W6943169523","doi":"10.15468/dl.ndzgnc","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":[0.0009435801,0.002057804,0.001550403,0.004943135,0.000959239,0.002505601,0.002682295,0.001966778,0.1635802],"category_scores_gemma":[0.006151519,0.0009036086,0.001225466,0.009800451,0.0004479203,0.002080067,0.002482599,0.001850984,0.2218955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489302,"about_ca_system_score_gemma":0.00231368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02129067,"about_ca_topic_score_gemma":0.03464727,"domain_scores_codex":[0.9989998,0.0001362724,0.0001242137,0.0003631271,0.000211223,0.0001653976],"domain_scores_gemma":[0.9976062,0.0007127253,0.0002242311,0.0006040077,0.0005918322,0.0002609575],"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":[0.00003044123,0.00001137585,0.0003893951,0.0005617928,0.00001466276,0.00001454134,0.00002244094,0.0001360678,0.0001159819,0.0003407575,0.9968625,0.00149988],"study_design_scores_gemma":[0.00007859497,0.00001038888,0.001843081,0.0001944667,0.00001554658,0.00003567968,0.00007026909,0.0001689004,0.0001898285,0.000793649,0.9965808,0.00001885371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004397809,0.00002695397,0.00004263047,0.00003456956,0.00001251375,0.000005492442,0.9988452,0.0003918975,0.0005967827],"genre_scores_gemma":[0.0001671381,0.00003536611,0.000215224,0.000047772,0.000003830235,0.00004879224,0.9988098,0.0001635817,0.0005084848],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8364198,"threshold_uncertainty_score":0.5472303,"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."}}