{"id":"W6943395185","doi":"10.15468/dl.ud4wfn","title":"Occurrence Download","year":2019,"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); Base (topology); Reference data","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":[0.0007755326,0.002921285,0.002187727,0.005921687,0.001220805,0.003327902,0.002537048,0.002528528,0.2928324],"category_scores_gemma":[0.005356996,0.001012847,0.001988685,0.008520676,0.0003976033,0.003690724,0.003740399,0.002175493,0.3578852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001387174,"about_ca_system_score_gemma":0.002647467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02152782,"about_ca_topic_score_gemma":0.03736788,"domain_scores_codex":[0.9988388,0.0001465611,0.0001722645,0.0004227331,0.0002289913,0.0001906578],"domain_scores_gemma":[0.9978987,0.0006059771,0.0001559127,0.0005364893,0.0005163533,0.0002864413],"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":[0.00006568473,0.00001963165,0.0003087268,0.0007876175,0.00001808069,0.00002629955,0.00003147367,0.000154289,0.0001205025,0.0005202935,0.9938419,0.004105446],"study_design_scores_gemma":[0.00008633019,0.00001585966,0.001219755,0.0002153351,0.00001858489,0.00005768232,0.00009157387,0.0003487056,0.0001825463,0.001312531,0.9964246,0.00002646292],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008544122,0.0001039966,0.0001827648,0.00007663227,0.00004475508,0.00001824782,0.9946003,0.002353558,0.002534322],"genre_scores_gemma":[0.0002964586,0.0001106896,0.0007941339,0.0001203619,0.00001086888,0.00007413855,0.9965024,0.00051046,0.001580505],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7071676,"threshold_uncertainty_score":0.979622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}