{"id":"W6962530060","doi":"10.15468/dl.t4pgbx","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":"Matching (statistics); Download; 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":[0.001007415,0.002133759,0.001715935,0.005273429,0.0009981238,0.002727371,0.002854851,0.00200176,0.1649334],"category_scores_gemma":[0.00615953,0.001019522,0.001233714,0.01031295,0.0004356736,0.002375544,0.002706482,0.002006955,0.2253976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001560816,"about_ca_system_score_gemma":0.002413488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01948372,"about_ca_topic_score_gemma":0.03260476,"domain_scores_codex":[0.9988075,0.0001636482,0.0001568907,0.0004279961,0.0002511262,0.0001927395],"domain_scores_gemma":[0.997327,0.0007449965,0.0002629722,0.0007050667,0.0006508326,0.0003091468],"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":[0.00003531942,0.00001131317,0.0003573005,0.0005835792,0.00001639937,0.00001349395,0.00002052026,0.0001161164,0.0001190198,0.0003816235,0.9969664,0.001378867],"study_design_scores_gemma":[0.0000812421,0.00000922144,0.001812499,0.0001870776,0.00001597867,0.00003518331,0.00005593116,0.0001350547,0.0001793294,0.0008285884,0.9966407,0.00001913081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003441305,0.00002570165,0.00003678854,0.00002901385,0.00001038445,0.000004562958,0.9989775,0.0003160874,0.0005654666],"genre_scores_gemma":[0.0001398398,0.00003521126,0.0001802544,0.00004758694,0.000003523015,0.00003874429,0.9989574,0.0001379614,0.0004594923],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8350666,"threshold_uncertainty_score":0.5517572,"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."}}