{"id":"W6924520463","doi":"10.15468/dl.qwkyx2","title":"Occurrence Download","year":2023,"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); Alien; Geocoding","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":[0.001097294,0.002050596,0.00167041,0.004969674,0.001069549,0.002639175,0.003023442,0.002247438,0.1491025],"category_scores_gemma":[0.005955186,0.0009170124,0.001275745,0.009441104,0.0004673129,0.002432864,0.002568707,0.002131965,0.2156165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001668238,"about_ca_system_score_gemma":0.002392913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02188024,"about_ca_topic_score_gemma":0.03599941,"domain_scores_codex":[0.9988919,0.000160165,0.0001371896,0.0003882239,0.0002417884,0.0001807419],"domain_scores_gemma":[0.9974196,0.0007488462,0.0002294405,0.0007015885,0.000612049,0.0002884241],"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":[0.00003029568,0.00001245496,0.0003458095,0.0005169691,0.00001518467,0.00001464731,0.00002188094,0.0001226537,0.000117723,0.0003804961,0.9970939,0.00132805],"study_design_scores_gemma":[0.00007812174,0.000009113374,0.001958019,0.0001980995,0.00001529111,0.00003930771,0.00007312966,0.0001574883,0.0002096046,0.0008494491,0.9963929,0.00001936092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004210252,0.00002798645,0.00004536541,0.00003791514,0.00001251733,0.000005495707,0.9988319,0.0003777789,0.0006189535],"genre_scores_gemma":[0.0001441512,0.00003067053,0.0001815851,0.00004255896,0.000003332858,0.00004005028,0.999,0.0001307619,0.000426831],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8508975,"threshold_uncertainty_score":0.4987976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}