{"id":"W6961802323","doi":"10.15468/dl.fb6ffy","title":"Occurrence Download","year":2025,"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); Dreissena","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":[0.001041365,0.001893845,0.001590309,0.0052338,0.0009330572,0.002595865,0.002754157,0.001994255,0.1713256],"category_scores_gemma":[0.006333613,0.0008975694,0.001210171,0.01006369,0.0004416975,0.002216554,0.002552539,0.001886485,0.2205143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001533794,"about_ca_system_score_gemma":0.002355892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02082405,"about_ca_topic_score_gemma":0.03238856,"domain_scores_codex":[0.9989266,0.0001393222,0.0001469384,0.0003663642,0.0002392913,0.0001814901],"domain_scores_gemma":[0.9974623,0.0007117949,0.0002449698,0.0006624539,0.0006222033,0.0002962968],"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":[0.00003148903,0.0000109725,0.0003845446,0.0006342933,0.00001742965,0.00001619171,0.00002201075,0.0001258531,0.0001337684,0.0003998389,0.9967974,0.001426383],"study_design_scores_gemma":[0.00007922569,0.000008354707,0.001933015,0.0002101398,0.00001616962,0.00003661499,0.00006261592,0.0001336793,0.0002007192,0.0007587732,0.996543,0.00001762046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003497421,0.00002436789,0.00003736907,0.00003021479,0.0000104816,0.000004969237,0.9989761,0.000312859,0.0005686202],"genre_scores_gemma":[0.0001433111,0.00003162959,0.0001635149,0.00004177265,0.000003277477,0.00003741395,0.9990529,0.0001242938,0.0004018173],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8286744,"threshold_uncertainty_score":0.5731412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437393559742932,"score_gpt":0.2320798631925623,"score_spread":0.217705927595133,"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."}}