{"id":"W6962047477","doi":"10.15468/dl.nggbdi","title":"Occurrence Download","year":2015,"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); Data set; Set (abstract data type)","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":[0.001005817,0.001870289,0.001580524,0.005126437,0.000970668,0.002684277,0.002903096,0.001910079,0.1520142],"category_scores_gemma":[0.006203132,0.0009111766,0.001167803,0.01082103,0.00042647,0.002560291,0.002732114,0.002036411,0.215501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671881,"about_ca_system_score_gemma":0.002547131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02548676,"about_ca_topic_score_gemma":0.04404834,"domain_scores_codex":[0.998869,0.0001582697,0.0001427691,0.000392449,0.0002549507,0.0001825898],"domain_scores_gemma":[0.9973438,0.0007013901,0.0002542227,0.0007375988,0.0006632008,0.0002998754],"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":[0.00002340023,0.000009339027,0.0003512272,0.0004462058,0.00001380519,0.00001223403,0.00002317232,0.0001125246,0.00008176992,0.000426303,0.9972364,0.001263653],"study_design_scores_gemma":[0.00005471803,0.000006218275,0.001610606,0.0001696019,0.00001195715,0.0000286887,0.00006515718,0.000131985,0.0001446935,0.0008058681,0.9969549,0.00001554485],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003906143,0.00002698447,0.00004700313,0.00003576537,0.0000113209,0.000004791769,0.9987378,0.0003967284,0.000700538],"genre_scores_gemma":[0.0001500117,0.00003377317,0.0001829141,0.00004119013,0.00000308437,0.00003401119,0.9989098,0.0001487901,0.0004964055],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8479858,"threshold_uncertainty_score":0.5085381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02668786630850237,"score_gpt":0.2410469455301918,"score_spread":0.2143590792216895,"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."}}