{"id":"W6905926245","doi":"10.15468/dl.u4k5qg","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; Alien; Range (aeronautics); State (computer science)","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":[0.0008908848,0.002046643,0.001481341,0.004585798,0.0009315259,0.002360282,0.002583563,0.001928897,0.1548256],"category_scores_gemma":[0.005648721,0.0008855627,0.001204405,0.009115049,0.0004336979,0.002121896,0.002489178,0.001792543,0.2095849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439253,"about_ca_system_score_gemma":0.002247662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02044605,"about_ca_topic_score_gemma":0.03305736,"domain_scores_codex":[0.999023,0.0001282822,0.000123784,0.0003543559,0.0002011207,0.0001695303],"domain_scores_gemma":[0.9977121,0.0006450586,0.0002200685,0.0005937709,0.0005586501,0.0002703726],"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":[0.00003422874,0.0000123493,0.0004206946,0.0005243794,0.00001448651,0.00001457324,0.00002077304,0.0001362495,0.0001298912,0.0003384883,0.9968722,0.001481618],"study_design_scores_gemma":[0.00008662135,0.0000121186,0.002121663,0.0001875752,0.00001599508,0.00003982483,0.00007063931,0.0001817455,0.0002222115,0.0007974836,0.9962445,0.00001959796],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005047386,0.0000250283,0.00003994704,0.00003306932,0.00001308369,0.000005215687,0.9988558,0.0003849916,0.000592378],"genre_scores_gemma":[0.0001693494,0.00003144513,0.0001906588,0.00004476258,0.00000364769,0.00004100842,0.9989127,0.0001434007,0.0004629935],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8451744,"threshold_uncertainty_score":0.5179431,"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."}}