{"id":"W7116792529","doi":"10.15468/dl.ev47sx","title":"Occurrence Download","year":2025,"lang":"","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Polygon (computer graphics); Data archive","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":[],"consensus_categories":[],"category_scores_codex":[0.0007614434,0.002548198,0.001995459,0.006272797,0.001605249,0.004131648,0.003032371,0.0027416,0.2871769],"category_scores_gemma":[0.006429239,0.0009913,0.00171645,0.009841563,0.000437887,0.004604687,0.003668514,0.002595802,0.4107646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00175046,"about_ca_system_score_gemma":0.002483525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01957425,"about_ca_topic_score_gemma":0.0434267,"domain_scores_codex":[0.9986725,0.0001481577,0.0001843434,0.0004556591,0.0003252851,0.0002141337],"domain_scores_gemma":[0.9974266,0.0006153352,0.00019212,0.0006125125,0.0008209298,0.0003325173],"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":[0.0000356562,0.00001270276,0.0003004981,0.0005252656,0.000009840303,0.00002585745,0.00002095468,0.00007979997,0.00009545033,0.000393215,0.9954976,0.003003107],"study_design_scores_gemma":[0.00004467158,0.00001014255,0.0009610705,0.0001701187,0.00001008516,0.00006034342,0.00007924251,0.0002248769,0.0001493832,0.001027838,0.9972442,0.00001803415],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000093606,0.0001287675,0.0001939335,0.0001118675,0.00004993033,0.00001588778,0.9933642,0.00230252,0.003739289],"genre_scores_gemma":[0.0003097414,0.0001059786,0.0005787148,0.0001254209,0.00001366511,0.00004989842,0.9964265,0.0005214278,0.001868619],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2871769,"threshold_uncertainty_score":0.9607025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434536157882973,"score_gpt":0.2311093459842124,"score_spread":0.2167639844053826,"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."}}