{"id":"W6924577210","doi":"10.15468/dl.fgu3ss","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); 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":[0.001020815,0.001801496,0.001442039,0.004563834,0.0009475779,0.002452944,0.002770451,0.001966253,0.1491419],"category_scores_gemma":[0.00601938,0.0008691077,0.001092784,0.009167036,0.0004329568,0.002168609,0.002496643,0.002024207,0.2099168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00165151,"about_ca_system_score_gemma":0.00234115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02395964,"about_ca_topic_score_gemma":0.03827735,"domain_scores_codex":[0.9990282,0.0001344907,0.0001191816,0.0003280967,0.0002293415,0.0001606364],"domain_scores_gemma":[0.9977,0.0006332583,0.0002234841,0.0005895983,0.0005891619,0.000264449],"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":[0.00002495385,0.00001064902,0.0003713295,0.0003809348,0.0000120572,0.00001310344,0.00002164146,0.0001288919,0.00008682058,0.0003946497,0.9972484,0.001306504],"study_design_scores_gemma":[0.00006827823,0.000007156393,0.001843257,0.0001582146,0.00001175029,0.00003217487,0.00006836155,0.0001643937,0.0001626223,0.000822855,0.9966452,0.00001594247],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004160215,0.00002222318,0.00004590696,0.00003822714,0.00001093972,0.00000500453,0.9988371,0.0003635762,0.0006354878],"genre_scores_gemma":[0.0001552936,0.00002793069,0.0001991575,0.00004201635,0.000003324168,0.00003984395,0.9988925,0.0001391571,0.0005006681],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8508581,"threshold_uncertainty_score":0.4989295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01233410479493285,"score_gpt":0.207945639435875,"score_spread":0.1956115346409421,"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."}}