{"id":"W6887106682","doi":"10.15468/dl.mq5s20","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":[0.001057343,0.001909871,0.00160063,0.006295591,0.0009450876,0.002788595,0.002702594,0.001799636,0.1908014],"category_scores_gemma":[0.006704724,0.000909682,0.001147999,0.01170387,0.0004156255,0.002525981,0.002932002,0.001972805,0.2640469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504232,"about_ca_system_score_gemma":0.002514759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02041684,"about_ca_topic_score_gemma":0.03695785,"domain_scores_codex":[0.9988171,0.0001569706,0.0001589764,0.0003963061,0.0002757593,0.0001950067],"domain_scores_gemma":[0.9970048,0.0007701371,0.0002935215,0.0007637923,0.000807091,0.0003606157],"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":[0.00002364261,0.000008156137,0.000313924,0.0004754118,0.0000131722,0.00001146694,0.00001969199,0.0000857158,0.0000845023,0.0003301206,0.9972572,0.001377067],"study_design_scores_gemma":[0.000052583,0.000006354918,0.001583127,0.0001802844,0.0000123394,0.00002849989,0.00005911908,0.000098081,0.0001349047,0.0006572584,0.997173,0.00001450231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003185432,0.00002475557,0.00004020413,0.00003092826,0.00001092533,0.000004969827,0.9988528,0.0003442235,0.0006592302],"genre_scores_gemma":[0.0001294571,0.00003393311,0.0001785989,0.00004203765,0.000003920259,0.0000368293,0.9989091,0.0001550828,0.0005109116],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8091986,"threshold_uncertainty_score":0.6382942,"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."}}