{"id":"W6943580078","doi":"10.15468/dl.pw6ndk","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); State (computer science); 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":[0.000902893,0.002037979,0.001534682,0.00502196,0.0009794757,0.002430176,0.002776176,0.001889122,0.1655716],"category_scores_gemma":[0.00539129,0.0009306968,0.001141883,0.0096606,0.0004461863,0.002267657,0.002545537,0.001914125,0.2232304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001467339,"about_ca_system_score_gemma":0.002191468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01942905,"about_ca_topic_score_gemma":0.03307572,"domain_scores_codex":[0.999011,0.0001334389,0.0001223514,0.0003590837,0.0002072238,0.0001669025],"domain_scores_gemma":[0.99782,0.0005943292,0.000212253,0.0005698064,0.000542838,0.0002607268],"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":[0.0000316566,0.00001104042,0.0003754103,0.0005385559,0.00001439494,0.00001446806,0.00002206106,0.0001235363,0.0001254158,0.0003765954,0.9968733,0.00149349],"study_design_scores_gemma":[0.00007031632,0.000008721052,0.001732297,0.000174056,0.00001373793,0.00003751853,0.00006344734,0.000130485,0.0001816817,0.000786229,0.9967839,0.00001772473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004354297,0.00002716156,0.0000413141,0.00003043023,0.00001230609,0.000004666031,0.9988279,0.0003390052,0.0006737029],"genre_scores_gemma":[0.0001496719,0.0000327764,0.0001885529,0.00004397925,0.00000339722,0.00003777228,0.9989221,0.0001424273,0.0004794126],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8344284,"threshold_uncertainty_score":0.5538921,"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."}}