{"id":"W6887005856","doi":"10.15468/dl.c7dumc","title":"Occurrence Download","year":2025,"lang":"en","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); Data set; Identification (biology)","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":[0.0009577295,0.001928645,0.001536952,0.00556569,0.0009616196,0.002622305,0.002686458,0.001869223,0.167385],"category_scores_gemma":[0.005779372,0.0008725792,0.001143598,0.01075732,0.0004494842,0.002285061,0.002756449,0.001885611,0.240561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001648635,"about_ca_system_score_gemma":0.00252709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0254127,"about_ca_topic_score_gemma":0.04448539,"domain_scores_codex":[0.9989503,0.0001390778,0.0001414104,0.0003490345,0.0002374921,0.0001827944],"domain_scores_gemma":[0.9973693,0.0006550067,0.0002525835,0.0007105665,0.0006979921,0.0003145149],"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":[0.00002880185,0.00001007083,0.0003467397,0.000537252,0.00001466666,0.00001393747,0.00002283003,0.0001119735,0.0001112119,0.0003918973,0.9969372,0.001473437],"study_design_scores_gemma":[0.00005651292,0.000006768972,0.001595902,0.000174154,0.00001251275,0.00003091998,0.00006280119,0.0001048399,0.0001563516,0.0006910204,0.9970925,0.00001581229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003457309,0.00002378583,0.00003667494,0.00002956883,0.00001042869,0.000004673794,0.9989032,0.0003176348,0.0006394152],"genre_scores_gemma":[0.000136879,0.00003325518,0.0001728364,0.00004205753,0.000003315712,0.00003289434,0.9989766,0.0001325034,0.0004697187],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.832615,"threshold_uncertainty_score":0.5599586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437393559742932,"score_gpt":0.2320798631925623,"score_spread":0.217705927595133,"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."}}