{"id":"W6887219505","doi":"10.15468/dl.uqtu6d","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":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0008982046,0.001991485,0.001476694,0.004685157,0.0009500224,0.00239818,0.002581342,0.00186647,0.1657733],"category_scores_gemma":[0.005637823,0.0008789917,0.001186572,0.009352718,0.0004322384,0.002124213,0.002459922,0.001764157,0.2258684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001406386,"about_ca_system_score_gemma":0.002191078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01964201,"about_ca_topic_score_gemma":0.03199687,"domain_scores_codex":[0.9990156,0.0001324207,0.000122295,0.0003589962,0.0002018931,0.0001687829],"domain_scores_gemma":[0.9977297,0.0006397483,0.0002144682,0.0005897092,0.0005645645,0.000261791],"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":[0.00003142168,0.00001132012,0.0003961123,0.0004925359,0.00001342284,0.0000137358,0.0000198714,0.0001264907,0.0001185446,0.0003362905,0.9969805,0.00145971],"study_design_scores_gemma":[0.00007898414,0.00001089519,0.001993816,0.0001814152,0.00001491277,0.00003673395,0.00006767563,0.0001595699,0.0001983502,0.0007996402,0.9964396,0.00001834743],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004720757,0.00002554363,0.00004040987,0.00003280112,0.00001269552,0.000004985032,0.9988424,0.0003665372,0.0006275442],"genre_scores_gemma":[0.0001632689,0.00003199988,0.0001857159,0.00004513099,0.000003796539,0.00004047769,0.9988981,0.0001433401,0.0004881277],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8342267,"threshold_uncertainty_score":0.554567,"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."}}