{"id":"W6962155338","doi":"10.15468/dl.xumwj7","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":[0.001009571,0.001909895,0.001585357,0.005044163,0.0009756279,0.002658497,0.002847061,0.002065823,0.162119],"category_scores_gemma":[0.006059707,0.0009196028,0.001193902,0.009420231,0.0004311177,0.002352892,0.002506648,0.00203954,0.2252706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001588643,"about_ca_system_score_gemma":0.002278855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01982339,"about_ca_topic_score_gemma":0.03115669,"domain_scores_codex":[0.9990144,0.0001361031,0.0001218627,0.0003518358,0.0002138556,0.0001619606],"domain_scores_gemma":[0.9976276,0.000711396,0.0002145551,0.0006076258,0.000580727,0.0002582309],"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":[0.00002904948,0.00001209203,0.000401839,0.0006179986,0.00001548763,0.0000159129,0.00002405762,0.0001316109,0.0001291989,0.0003918097,0.99669,0.001540968],"study_design_scores_gemma":[0.00007405725,0.000008770984,0.001840534,0.0002151163,0.00001566412,0.00003734466,0.00007605265,0.0001627496,0.0001998349,0.0007803292,0.9965713,0.00001828243],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004010332,0.00002794336,0.00004431927,0.00003568744,0.00001196741,0.000005627039,0.9988636,0.0003651743,0.0006056477],"genre_scores_gemma":[0.0001613066,0.00003651271,0.0001997036,0.0000465853,0.0000036604,0.00004827701,0.9988864,0.0001498558,0.0004676583],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.837881,"threshold_uncertainty_score":0.5423422,"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."}}