{"id":"W6887162285","doi":"10.15468/dl.s8mt8s","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":"Download; Matching (statistics); 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":[0.0009376049,0.001907155,0.001512155,0.004990595,0.0009865866,0.002522927,0.002626255,0.002063985,0.1667108],"category_scores_gemma":[0.005724541,0.0008562837,0.001198152,0.00954641,0.0004484977,0.002247155,0.002491936,0.001889961,0.2366198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468123,"about_ca_system_score_gemma":0.00218802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02050184,"about_ca_topic_score_gemma":0.03293105,"domain_scores_codex":[0.9990515,0.0001347865,0.0001188838,0.000331908,0.0002023719,0.0001605514],"domain_scores_gemma":[0.997535,0.0007242538,0.0002258457,0.0006333942,0.0006076552,0.0002738959],"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":[0.00002629747,0.00001139187,0.0004055157,0.0005318869,0.00001319888,0.0000152609,0.00002368867,0.0001236019,0.0001129252,0.0003253072,0.9968978,0.001513139],"study_design_scores_gemma":[0.00006945422,0.000009199368,0.002025003,0.0002117369,0.00001419176,0.00003703851,0.00008582465,0.0001601211,0.0001822232,0.0007111891,0.9964765,0.00001761353],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004682184,0.0000284188,0.00004340392,0.00003875601,0.00001371138,0.0000057712,0.9988128,0.0003762787,0.0006339368],"genre_scores_gemma":[0.0001716362,0.0000351548,0.0002036661,0.00004857482,0.000004215928,0.0000473203,0.9988443,0.0001464709,0.0004987445],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8332893,"threshold_uncertainty_score":0.5577031,"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."}}