{"id":"W7107969241","doi":"10.15468/dl.dteqdz","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); Order (exchange)","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":[0.0008756446,0.0017996,0.001632373,0.005525878,0.001072671,0.002912698,0.002716595,0.0019564,0.19006],"category_scores_gemma":[0.006402028,0.0009329235,0.001200089,0.01049587,0.0004029355,0.002559855,0.002653164,0.001897106,0.2604903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001669434,"about_ca_system_score_gemma":0.002521039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02338926,"about_ca_topic_score_gemma":0.0377848,"domain_scores_codex":[0.9989154,0.0001276109,0.0001455888,0.0003864327,0.0002427745,0.0001821105],"domain_scores_gemma":[0.9974745,0.000676366,0.0002361759,0.0006296213,0.0007060398,0.0002772261],"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":[0.00002999164,0.000009193688,0.0004242441,0.0006136714,0.00001424673,0.00001611675,0.0000241411,0.0001021869,0.0001100628,0.0004057343,0.996415,0.001835356],"study_design_scores_gemma":[0.00005136317,0.000006285815,0.00157693,0.0001966418,0.00001252584,0.00003357431,0.00007019428,0.0001186811,0.0001564363,0.0006403447,0.997122,0.00001500484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003855488,0.00003099902,0.00004680988,0.00003569932,0.00001218921,0.000004675431,0.9986349,0.0004260564,0.0007702351],"genre_scores_gemma":[0.0001709686,0.00004293618,0.0002158239,0.00005040308,0.000004067976,0.00003828154,0.9986848,0.0001753891,0.0006172038],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.80994,"threshold_uncertainty_score":0.6358142,"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."}}