{"id":"W6887113418","doi":"10.15468/dl.kqa72g","title":"Occurrence Download","year":2016,"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); Invertebrate; Atlantic forest","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":[0.001049998,0.001919655,0.001567506,0.005712563,0.0008573642,0.002585058,0.002716254,0.00180322,0.1835925],"category_scores_gemma":[0.006559546,0.0008881277,0.001169784,0.01104118,0.0003924409,0.002409932,0.002865521,0.001863007,0.2594938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001496152,"about_ca_system_score_gemma":0.002447485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02066186,"about_ca_topic_score_gemma":0.03590172,"domain_scores_codex":[0.9988946,0.0001458431,0.0001479591,0.0003676273,0.0002568527,0.0001870981],"domain_scores_gemma":[0.9972059,0.0006872469,0.0002816424,0.0007467733,0.0007349155,0.0003434955],"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":[0.00002496616,0.000007872498,0.0003141565,0.0004677051,0.00001362585,0.00001077839,0.00001753916,0.00009355864,0.00008688838,0.0003206611,0.9972269,0.001415189],"study_design_scores_gemma":[0.0000575244,0.000006813485,0.001636246,0.0001759908,0.00001280867,0.00002820588,0.0000513789,0.0001062911,0.0001508357,0.000676016,0.9970829,0.00001492668],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003247175,0.00002462218,0.00004037708,0.00002953343,0.00001089783,0.000004865598,0.9988862,0.0003504235,0.0006205688],"genre_scores_gemma":[0.0001332175,0.00003334821,0.0001708356,0.00003991897,0.000003750031,0.0000367829,0.9989377,0.0001455773,0.0004988427],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8164074,"threshold_uncertainty_score":0.6141782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734962626846364,"score_gpt":0.227796013577581,"score_spread":0.2104463873091174,"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."}}