{"id":"W6905983795","doi":"10.15468/dl.z374sq","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":"Matching (statistics); Download; Range (aeronautics); Work (physics); Process (computing)","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":[0.0009129703,0.002056685,0.001684632,0.005423895,0.001011607,0.002533006,0.002833198,0.001930546,0.1491838],"category_scores_gemma":[0.005201183,0.0008898218,0.001212527,0.0111324,0.0004460931,0.002212577,0.002605963,0.001961695,0.231878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001743134,"about_ca_system_score_gemma":0.002647344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03238815,"about_ca_topic_score_gemma":0.05516006,"domain_scores_codex":[0.9989729,0.0001284217,0.0001187416,0.0003544247,0.000243104,0.0001825237],"domain_scores_gemma":[0.9976346,0.0005759273,0.000212837,0.0006314836,0.0006537928,0.0002912723],"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":[0.00002663817,0.000009245769,0.0003487772,0.0004832848,0.00001464503,0.00001304613,0.00002175948,0.0001179903,0.0001160309,0.0003401429,0.997116,0.001392582],"study_design_scores_gemma":[0.00005932375,0.000006752031,0.001859276,0.0001727054,0.00001386721,0.0000317085,0.00006820501,0.0001298407,0.0001890842,0.0007028439,0.9967488,0.0000175995],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000348044,0.00002539242,0.00003925413,0.0000264354,0.000009945093,0.000004233636,0.9989167,0.0003603932,0.0005828188],"genre_scores_gemma":[0.000131167,0.00003037325,0.0001710759,0.00003371905,0.000002827649,0.00003147452,0.9990267,0.0001391436,0.000433566],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8508162,"threshold_uncertainty_score":0.4990695,"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."}}