{"id":"W6887215187","doi":"10.15468/dl.v47e73","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; 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":[0.001107133,0.001967551,0.001617933,0.005230749,0.0009980025,0.002630295,0.002884801,0.002165915,0.1505007],"category_scores_gemma":[0.006140091,0.0008990609,0.001258904,0.01023211,0.0004677579,0.002299327,0.002518738,0.002064718,0.22079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001625396,"about_ca_system_score_gemma":0.002440099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02128995,"about_ca_topic_score_gemma":0.0333931,"domain_scores_codex":[0.9988354,0.0001647665,0.0001541412,0.0003977522,0.0002567736,0.0001911522],"domain_scores_gemma":[0.9972235,0.0007888249,0.0002589273,0.0007278172,0.0006995033,0.0003015305],"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":[0.00003021255,0.00001238747,0.0003788332,0.0005403854,0.00001542472,0.00001535574,0.00002174894,0.0001223766,0.0001186383,0.0003643683,0.9970283,0.001352017],"study_design_scores_gemma":[0.00007810584,0.000009089649,0.001969112,0.0002033354,0.00001541978,0.00003817251,0.0000758403,0.0001467309,0.0002017384,0.0007921385,0.9964515,0.00001877899],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003823741,0.0000251755,0.00003861927,0.00003364542,0.00001132915,0.000005177787,0.9989995,0.0003042483,0.0005441272],"genre_scores_gemma":[0.000145914,0.0000311823,0.0001717105,0.0000417906,0.000003409878,0.00004082537,0.999041,0.0001154473,0.0004086137],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8494993,"threshold_uncertainty_score":0.503475,"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."}}