{"id":"W6962095306","doi":"10.15468/dl.rpb865","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Range (aeronautics); State (computer science); Identification (biology)","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":[0.001015239,0.001985794,0.001409851,0.004782765,0.001014396,0.002386588,0.002682327,0.001984978,0.1416702],"category_scores_gemma":[0.006104889,0.0008843847,0.001193421,0.009045308,0.0004723213,0.002197564,0.00245535,0.002026362,0.1943865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589596,"about_ca_system_score_gemma":0.00240116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02214493,"about_ca_topic_score_gemma":0.03887764,"domain_scores_codex":[0.9989375,0.0001615574,0.0001329612,0.0003841687,0.0002201128,0.0001636014],"domain_scores_gemma":[0.9975063,0.000744515,0.0002304846,0.0006214083,0.000591848,0.00030548],"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":[0.00002811646,0.00001172153,0.0004058733,0.0004309555,0.00001234266,0.00001292115,0.00002004935,0.0001276673,0.00009586031,0.0003433885,0.9972034,0.001307752],"study_design_scores_gemma":[0.00007503617,0.000009105169,0.001849751,0.0001739986,0.00001301051,0.00003929206,0.00007227363,0.0001792449,0.0001682235,0.0008332969,0.9965692,0.00001764748],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005023084,0.00002801661,0.00004665048,0.00003970991,0.00001452947,0.000005410309,0.9987807,0.0003653681,0.000669342],"genre_scores_gemma":[0.0001607674,0.00003271724,0.0002107156,0.00005037188,0.000003809036,0.00004088583,0.9988865,0.0001383408,0.0004758544],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8583298,"threshold_uncertainty_score":0.4739339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08519950732304557,"score_gpt":0.3897100011914083,"score_spread":0.3045104938683627,"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."}}