{"id":"W6887082852","doi":"10.15468/dl.n2kn5a","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); Data compression; The Internet","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":[0.000924475,0.002027906,0.001633712,0.005390583,0.0009719859,0.002471318,0.002806905,0.001946987,0.1494348],"category_scores_gemma":[0.005759236,0.000908771,0.001160559,0.01094758,0.0004471805,0.002133618,0.002545038,0.001860384,0.2035407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00164772,"about_ca_system_score_gemma":0.002579936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02831193,"about_ca_topic_score_gemma":0.04688288,"domain_scores_codex":[0.9990049,0.0001280357,0.0001319126,0.0003426736,0.0002232518,0.0001691406],"domain_scores_gemma":[0.9976272,0.0006442687,0.0002263612,0.0006044964,0.0006179847,0.0002798384],"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":[0.00003369646,0.0000117201,0.0004383244,0.0006565525,0.00001812285,0.00001854045,0.00002847255,0.0001472656,0.0001469553,0.0003990247,0.9965907,0.001510514],"study_design_scores_gemma":[0.00007366722,0.000007793014,0.002092811,0.0001965173,0.00001612419,0.00004039688,0.00008266712,0.0001399797,0.0002052962,0.0006684638,0.9964573,0.00001905104],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004165836,0.00002566604,0.00003917275,0.00002855543,0.000009580526,0.000004694877,0.998973,0.000327375,0.0005502124],"genre_scores_gemma":[0.0001572654,0.00003174694,0.0001698589,0.00003532691,0.000002733844,0.00003629631,0.9990425,0.0001282505,0.0003960647],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8505653,"threshold_uncertainty_score":0.4999091,"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."}}