{"id":"W6905953290","doi":"10.15468/dl.t9x4gy","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":[0.0009488496,0.002093298,0.001575187,0.004603446,0.0009718386,0.002512833,0.002733638,0.002003837,0.1575764],"category_scores_gemma":[0.006105442,0.0009183095,0.001231158,0.009338144,0.0004390895,0.002102483,0.002424899,0.001881272,0.2142323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001492921,"about_ca_system_score_gemma":0.002330081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02133502,"about_ca_topic_score_gemma":0.03475657,"domain_scores_codex":[0.9989857,0.0001411003,0.0001240607,0.0003748197,0.0002095622,0.0001647017],"domain_scores_gemma":[0.997623,0.0007173363,0.0002172653,0.000600672,0.0005825707,0.0002590387],"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":[0.00003103085,0.00001177526,0.0003827695,0.0005397247,0.0000150788,0.00001388073,0.00002062247,0.0001304953,0.0001143678,0.0003361549,0.997045,0.001359132],"study_design_scores_gemma":[0.00008704521,0.0000112676,0.001973429,0.0001999741,0.00001709216,0.00003770515,0.00006873836,0.0001799905,0.00020574,0.0008354667,0.9963637,0.00001974491],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004431476,0.00002773078,0.00004218724,0.00003555047,0.00001237154,0.000005503757,0.9988612,0.0003837442,0.0005874555],"genre_scores_gemma":[0.0001653278,0.00003446415,0.0001996416,0.00004932456,0.000003711923,0.0000471919,0.9988574,0.0001530506,0.0004899489],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8424236,"threshold_uncertainty_score":0.5271455,"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."}}