{"id":"W6924711045","doi":"10.15468/dl.wkvc78","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":[0.0009319116,0.002007568,0.001529909,0.004877174,0.001002202,0.002449336,0.002681604,0.001932464,0.1701312],"category_scores_gemma":[0.00583631,0.0009062302,0.001192847,0.009856295,0.000456806,0.002202416,0.002573007,0.001850046,0.2264772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001514106,"about_ca_system_score_gemma":0.002304868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02120673,"about_ca_topic_score_gemma":0.03454302,"domain_scores_codex":[0.9989993,0.0001360979,0.0001253355,0.0003614678,0.0002072949,0.0001704872],"domain_scores_gemma":[0.9976501,0.0006700911,0.0002233254,0.0006061983,0.0005862374,0.0002640577],"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":[0.00003009774,0.00001124354,0.0003882573,0.0005278945,0.00001341176,0.00001420513,0.00002294221,0.0001305606,0.0001221273,0.0003765752,0.9968741,0.001488543],"study_design_scores_gemma":[0.00007071581,0.000009383698,0.001748748,0.000178994,0.00001375441,0.00003340786,0.00006782349,0.0001458843,0.0001838649,0.000780506,0.996749,0.00001790438],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004440325,0.00002480939,0.00004270793,0.00003273897,0.00001240334,0.000005146745,0.9987972,0.0003823232,0.0006582242],"genre_scores_gemma":[0.0001625663,0.00003349857,0.0002098871,0.00004634695,0.00000371344,0.00004496489,0.9988342,0.0001650291,0.0004997584],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8298688,"threshold_uncertainty_score":0.5691454,"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."}}