{"id":"W6925015554","doi":"10.15468/dl.wsjgxd","title":"Occurrence Download","year":2018,"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":[0.001048144,0.001864668,0.001570019,0.006319246,0.0009192695,0.002731534,0.002638529,0.001778635,0.1958226],"category_scores_gemma":[0.006667627,0.0008761854,0.001119947,0.01174346,0.0004098403,0.002468841,0.002950825,0.001913967,0.2654045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483602,"about_ca_system_score_gemma":0.002476443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01991268,"about_ca_topic_score_gemma":0.03555504,"domain_scores_codex":[0.9988563,0.0001507289,0.0001556209,0.0003785441,0.0002662598,0.0001925788],"domain_scores_gemma":[0.9970535,0.0007581049,0.0002936503,0.0007462355,0.0007889071,0.0003595921],"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":[0.00002405185,0.00000803712,0.000319279,0.0004897661,0.00001322199,0.00001159954,0.00001997451,0.00008547695,0.00008517546,0.0003405115,0.997165,0.001437931],"study_design_scores_gemma":[0.00005109315,0.000006409351,0.00160354,0.0001801335,0.00001215257,0.00002807883,0.00005812323,0.00009338033,0.0001306638,0.0006460878,0.9971762,0.00001416938],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003228997,0.00002493349,0.00003952264,0.00003067868,0.00001096627,0.000004834937,0.9988531,0.0003332229,0.000670468],"genre_scores_gemma":[0.0001347178,0.00003491734,0.0001771036,0.00004221188,0.00000403245,0.0000371399,0.9988833,0.0001537994,0.0005328459],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8041773,"threshold_uncertainty_score":0.655092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881883250631837,"score_gpt":0.2330296220854826,"score_spread":0.2142107895791642,"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."}}