{"id":"W6961800266","doi":"10.15468/dl.mk7y62","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":[0.0008830791,0.002070451,0.00149442,0.004891682,0.0009474659,0.002402117,0.002584977,0.001950388,0.1558763],"category_scores_gemma":[0.00570798,0.0008650409,0.001201579,0.009713956,0.0004385884,0.002067039,0.002426734,0.001762273,0.2115422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450351,"about_ca_system_score_gemma":0.002233424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02107903,"about_ca_topic_score_gemma":0.03393907,"domain_scores_codex":[0.9990206,0.0001342586,0.0001239815,0.0003533342,0.0002021141,0.0001657135],"domain_scores_gemma":[0.9977109,0.0006630913,0.0002211573,0.0005756967,0.0005695467,0.0002595185],"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":[0.000032141,0.00001172925,0.0004253857,0.0005491857,0.00001447437,0.00001485215,0.00002181348,0.0001393573,0.0001209452,0.0003428806,0.9968494,0.00147783],"study_design_scores_gemma":[0.00008286797,0.00001119205,0.002035256,0.00019778,0.00001602995,0.0000383976,0.00007185838,0.0001720055,0.0001984355,0.0007857062,0.9963714,0.00001919357],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004907031,0.00002829717,0.0000384265,0.00003354052,0.00001244634,0.000005116546,0.9988574,0.0003559995,0.0006196923],"genre_scores_gemma":[0.0001710653,0.0000348987,0.0001873267,0.00004481924,0.000003714502,0.00004215335,0.9989169,0.0001370144,0.0004621645],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8441237,"threshold_uncertainty_score":0.5214582,"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."}}