{"id":"W6887111849","doi":"10.15468/dl.qubvkv","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":[0.0008902267,0.001988847,0.001461894,0.004816895,0.0009318339,0.002386699,0.002522837,0.001852793,0.1653318],"category_scores_gemma":[0.005811738,0.0008815936,0.00115335,0.009425447,0.0004269744,0.002127381,0.002487224,0.001728301,0.2216178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001397454,"about_ca_system_score_gemma":0.002180878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01959075,"about_ca_topic_score_gemma":0.031555,"domain_scores_codex":[0.9990238,0.0001292103,0.00012503,0.0003521403,0.000202985,0.0001669094],"domain_scores_gemma":[0.9976838,0.0006467326,0.0002215603,0.0005956671,0.0005867865,0.0002654569],"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":[0.00003286652,0.00001161534,0.0004214938,0.0005303244,0.00001394945,0.0000144386,0.00002134903,0.0001301775,0.0001262169,0.0003444776,0.9968275,0.001525532],"study_design_scores_gemma":[0.00007865243,0.00001080584,0.002015982,0.0001865201,0.00001489569,0.00003756101,0.00007016277,0.0001609301,0.0002047528,0.0007836843,0.9964175,0.00001856479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004870595,0.00002551271,0.00004113285,0.00003194957,0.00001248572,0.000005127932,0.9988116,0.0003867492,0.0006367766],"genre_scores_gemma":[0.0001715878,0.00003261066,0.000197268,0.0000450802,0.000003713998,0.0000410964,0.9988632,0.0001542652,0.0004911833],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8346683,"threshold_uncertainty_score":0.5530898,"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."}}