{"id":"W6887239592","doi":"10.15468/dl.v6rjhr","title":"Occurrence Download","year":2022,"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); Alien; UniProt","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":[0.0009975248,0.00197445,0.001601153,0.004727252,0.001027387,0.002691495,0.002673405,0.00214581,0.1740086],"category_scores_gemma":[0.006556238,0.0008944562,0.001276565,0.008967608,0.0004318492,0.002557621,0.002635923,0.002004068,0.2434491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548459,"about_ca_system_score_gemma":0.002342279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02091989,"about_ca_topic_score_gemma":0.03352541,"domain_scores_codex":[0.9989215,0.0001551373,0.0001328548,0.0003889095,0.0002282636,0.0001732741],"domain_scores_gemma":[0.9971606,0.0008437076,0.0002361703,0.0007474233,0.000711918,0.0003002538],"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":[0.0000277277,0.00001156585,0.0003655004,0.0005063968,0.00001267148,0.00001391326,0.0000207481,0.0001131114,0.00009391359,0.0003178541,0.9971685,0.001347992],"study_design_scores_gemma":[0.00007366329,0.000009572891,0.001773994,0.0002081822,0.00001389578,0.00003417699,0.00007547499,0.0001692123,0.0001778679,0.0008120434,0.9966341,0.00001791584],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004231718,0.00002822028,0.00004340127,0.00004403625,0.0000142559,0.000006271679,0.9987087,0.0004427708,0.0006698439],"genre_scores_gemma":[0.0001677194,0.00003648576,0.0002082993,0.00005510341,0.000004396381,0.00004764566,0.9987966,0.0001672951,0.000516572],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8259914,"threshold_uncertainty_score":0.5821167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}