{"id":"W6905853388","doi":"10.15468/dl.qr8jjm","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Identification (biology); Download","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":[0.0008666703,0.002149844,0.001427818,0.004443009,0.0009736856,0.002355142,0.002782743,0.001901281,0.1368563],"category_scores_gemma":[0.005936645,0.0008880181,0.001252951,0.008623872,0.0004288864,0.002263594,0.002465892,0.001872572,0.1876909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719689,"about_ca_system_score_gemma":0.00247713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0282864,"about_ca_topic_score_gemma":0.04674788,"domain_scores_codex":[0.9989531,0.0001344071,0.0001426987,0.0003640154,0.0002434688,0.0001622841],"domain_scores_gemma":[0.9977654,0.000610952,0.0002102061,0.00056595,0.0005897613,0.0002578433],"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":[0.00003298836,0.00001198542,0.000387809,0.0004638638,0.00001366818,0.00001534696,0.00002219279,0.0001291641,0.0001059239,0.000395151,0.9969702,0.001451628],"study_design_scores_gemma":[0.00008321514,0.000009534839,0.001821304,0.0001675368,0.00001392766,0.00004252055,0.00006989018,0.0002144053,0.0002030584,0.0008311248,0.9965252,0.00001833774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005301054,0.00002867608,0.00005200937,0.00003907969,0.00001203287,0.000005890751,0.9985378,0.0005533659,0.0007182296],"genre_scores_gemma":[0.0001627572,0.00003279448,0.0002223849,0.00004693078,0.000003107963,0.0000361699,0.998868,0.000167209,0.0004605329],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8631437,"threshold_uncertainty_score":0.4578301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009531274594205537,"score_gpt":0.2014603252339924,"score_spread":0.1919290506397869,"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."}}