{"id":"W6924650218","doi":"10.15468/dl.yrtv36","title":"Occurrence Download","year":2021,"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); Margin (machine learning); 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":[0.0008322356,0.00172745,0.001447008,0.00481503,0.0009710094,0.002609935,0.002472359,0.001831967,0.1829501],"category_scores_gemma":[0.005641074,0.0008435063,0.001133762,0.009835386,0.0003857343,0.002450613,0.002466393,0.001826178,0.2471995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001542297,"about_ca_system_score_gemma":0.002222895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02207372,"about_ca_topic_score_gemma":0.03734808,"domain_scores_codex":[0.9990332,0.0001241435,0.0001272687,0.000340246,0.0002163886,0.0001587234],"domain_scores_gemma":[0.9977524,0.0006213186,0.0002052713,0.0005459898,0.0006309928,0.0002440655],"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":[0.00002489957,0.000009305974,0.000373604,0.0005068237,0.00001262957,0.00001434736,0.00002161122,0.0001148091,0.00009945931,0.000368077,0.9967231,0.001731335],"study_design_scores_gemma":[0.0000548805,0.000007022988,0.001596964,0.0001852088,0.00001207969,0.00003454424,0.00007143418,0.0001529087,0.0001649589,0.0007175886,0.996987,0.00001537588],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004047271,0.00002854395,0.0000520987,0.0000389431,0.00001268158,0.00000540099,0.9985982,0.000419704,0.0008039475],"genre_scores_gemma":[0.000180748,0.00004037155,0.0002319211,0.00005094815,0.000004221078,0.0000422046,0.9986503,0.0001674714,0.0006319556],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8170499,"threshold_uncertainty_score":0.6120291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878725496536469,"score_gpt":0.2292776369319846,"score_spread":0.2104903819666199,"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."}}