{"id":"W7105896371","doi":"10.15468/dl.y8gtj5","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); Herbarium; Polygon (computer graphics); Data collection","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":[0.0008833968,0.001895061,0.001635033,0.005209622,0.001186428,0.002789143,0.002868863,0.002213852,0.1536349],"category_scores_gemma":[0.006547051,0.0008948194,0.001294544,0.01005621,0.0004207665,0.00259848,0.002596244,0.002001868,0.2119903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001925672,"about_ca_system_score_gemma":0.002808148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02789406,"about_ca_topic_score_gemma":0.04674543,"domain_scores_codex":[0.9988306,0.0001431034,0.0001510545,0.0004173529,0.0002587808,0.0001991402],"domain_scores_gemma":[0.9972899,0.0007327739,0.0002410123,0.0006992631,0.00074186,0.0002952373],"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":[0.00003502082,0.00001189516,0.0004775331,0.0005766931,0.00001482076,0.00001753163,0.00002304223,0.0001246422,0.0001192479,0.000393218,0.9964374,0.001768967],"study_design_scores_gemma":[0.00006849621,0.000009197051,0.002013999,0.0002047841,0.00001408779,0.00004283813,0.00008680833,0.0001844295,0.0001949172,0.0007544513,0.9964079,0.00001802878],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000485682,0.00002984101,0.00004769799,0.00004012439,0.00001374401,0.000005355778,0.9987405,0.0004444346,0.0006296715],"genre_scores_gemma":[0.0001710857,0.00003565197,0.0002196208,0.00004556384,0.000003867829,0.00003863108,0.9988381,0.0001395303,0.0005080247],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8463651,"threshold_uncertainty_score":0.51396,"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."}}