{"id":"W6887292976","doi":"10.15468/dl.zujf9z","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":[0.0008790864,0.001978605,0.001482062,0.004826404,0.0009539261,0.002433066,0.002548955,0.001927735,0.155175],"category_scores_gemma":[0.005695658,0.0008360134,0.001160125,0.00960579,0.0004282254,0.002089873,0.002398491,0.001741585,0.2181184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450466,"about_ca_system_score_gemma":0.002194077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0204345,"about_ca_topic_score_gemma":0.03315456,"domain_scores_codex":[0.9990193,0.0001325039,0.0001255373,0.0003504273,0.0002059141,0.0001663464],"domain_scores_gemma":[0.9977016,0.0006508573,0.0002226308,0.0005728069,0.0005983121,0.0002537158],"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":[0.00003208757,0.0000118495,0.000431335,0.0005285142,0.00001376071,0.00001473649,0.00002093046,0.0001281315,0.0001238142,0.0003438909,0.9968657,0.001485213],"study_design_scores_gemma":[0.00007780462,0.00001110995,0.002095634,0.0001917491,0.00001511819,0.00003837722,0.00007094332,0.0001661702,0.0002049851,0.0007760098,0.9963329,0.00001928369],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004945915,0.00002727133,0.00003873566,0.00003344895,0.00001217184,0.00000513648,0.9988472,0.0003550222,0.0006314775],"genre_scores_gemma":[0.0001735212,0.00003346449,0.0001848854,0.00004436899,0.000003850385,0.00004225623,0.9988996,0.0001359459,0.0004820259],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.844825,"threshold_uncertainty_score":0.5191119,"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."}}