{"id":"W6887230565","doi":"10.15468/dl.vwnd2x","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":"Download; Matching (statistics); Range (aeronautics); State (computer science); Data set","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":[0.001176617,0.00201933,0.001653544,0.005196202,0.001072505,0.002760883,0.002986058,0.002116513,0.1667769],"category_scores_gemma":[0.006531188,0.0009744944,0.00119929,0.01024375,0.0004696411,0.002390554,0.002619284,0.002094281,0.2314069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001679168,"about_ca_system_score_gemma":0.002484699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02274441,"about_ca_topic_score_gemma":0.036348,"domain_scores_codex":[0.9988427,0.0001582891,0.0001507429,0.0003977695,0.0002654018,0.0001850469],"domain_scores_gemma":[0.9972402,0.0007890993,0.0002499794,0.0007229517,0.0007012362,0.0002964855],"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":[0.00002751967,0.00001091325,0.0003440833,0.0005143344,0.00001509296,0.00001497252,0.00002356451,0.000117193,0.0001162206,0.000395768,0.9971114,0.001308897],"study_design_scores_gemma":[0.00006720672,0.000006951333,0.001678468,0.0001789738,0.00001408038,0.000034863,0.00006823943,0.0001381349,0.0001893529,0.0007649064,0.9968411,0.0000177816],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003475636,0.00002412753,0.00004725684,0.00003322686,0.00001088017,0.000005096297,0.9988403,0.0003664836,0.0006379157],"genre_scores_gemma":[0.0001458805,0.00003137468,0.0002005907,0.00004194202,0.000003165667,0.00004253142,0.9989366,0.0001620562,0.0004358517],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8332231,"threshold_uncertainty_score":0.5579243,"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."}}