{"id":"W6905842155","doi":"10.15468/dl.q6hdah","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); Range (aeronautics); UniProt; Set (abstract data type)","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":[0.001098312,0.001937639,0.001587774,0.004928465,0.001049561,0.002673821,0.002905068,0.002065984,0.1692077],"category_scores_gemma":[0.006383231,0.0009663316,0.001151873,0.009756855,0.0004644975,0.002309162,0.002642208,0.002074263,0.2300607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00170095,"about_ca_system_score_gemma":0.002455498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02352014,"about_ca_topic_score_gemma":0.03805349,"domain_scores_codex":[0.9989228,0.0001405738,0.0001362496,0.0003778594,0.0002480576,0.0001744626],"domain_scores_gemma":[0.9974178,0.0007416771,0.0002420088,0.0006620868,0.0006488027,0.0002876684],"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":[0.00002733125,0.00001047773,0.0003668945,0.0005025141,0.00001403355,0.00001478595,0.00002444977,0.0001157975,0.0001229742,0.0004011881,0.997068,0.00133149],"study_design_scores_gemma":[0.00006320026,0.000006839507,0.001710817,0.0001769296,0.00001338055,0.00003442429,0.00006996124,0.000131739,0.0001896889,0.0007025003,0.9968832,0.00001719598],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003680136,0.00002272858,0.00004645553,0.00003430804,0.00001094965,0.000004827909,0.9988148,0.0003770253,0.0006521465],"genre_scores_gemma":[0.0001595201,0.00003019655,0.0002084607,0.00004313777,0.000003117826,0.00004176056,0.9988551,0.0001786383,0.0004799563],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8307923,"threshold_uncertainty_score":0.5660561,"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."}}