{"id":"W6887033822","doi":"10.15468/dl.mmzmhf","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":[0.0008754235,0.001973198,0.001450852,0.004908437,0.0009362039,0.002397496,0.002490024,0.001866598,0.1684437],"category_scores_gemma":[0.005714237,0.0008694387,0.001138449,0.009881764,0.0004269211,0.002064546,0.002430706,0.001716362,0.2219875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441516,"about_ca_system_score_gemma":0.002214284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02068166,"about_ca_topic_score_gemma":0.03302202,"domain_scores_codex":[0.9990407,0.0001277518,0.0001208871,0.0003449496,0.0001998301,0.0001658909],"domain_scores_gemma":[0.9977244,0.0006557403,0.0002233259,0.0005675241,0.0005710971,0.0002578459],"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":[0.00003278583,0.00001165254,0.0004270106,0.0005532374,0.00001397582,0.00001512238,0.00002247731,0.0001309782,0.0001298617,0.0003728819,0.9967862,0.001503747],"study_design_scores_gemma":[0.00007443675,0.00001007212,0.001931945,0.0001886315,0.00001484551,0.00003580596,0.00006815961,0.0001448929,0.0001957797,0.0007823781,0.9965348,0.00001808244],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004646213,0.00002636896,0.00003797159,0.00003240129,0.00001160785,0.000004881774,0.9988434,0.0003399921,0.0006568038],"genre_scores_gemma":[0.0001736011,0.00003485891,0.0001888034,0.00004695814,0.000003716542,0.00004197467,0.9988537,0.0001484082,0.0005078918],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8315563,"threshold_uncertainty_score":0.5635003,"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."}}