{"id":"W6887185448","doi":"10.15468/dl.spetmk","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); Identification (biology); 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":[0.0009996778,0.002076911,0.001539182,0.005417475,0.0008938076,0.002515625,0.002856703,0.002044082,0.1288618],"category_scores_gemma":[0.00589574,0.000865948,0.001177189,0.01035245,0.0004406854,0.002192208,0.002622789,0.00193752,0.1953543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001673506,"about_ca_system_score_gemma":0.002447844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02204283,"about_ca_topic_score_gemma":0.03808688,"domain_scores_codex":[0.9988808,0.0001508929,0.0001560824,0.0003645772,0.0002578554,0.000189776],"domain_scores_gemma":[0.9974432,0.0006301942,0.0002740321,0.0007067836,0.0006304929,0.000315258],"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":[0.00003322764,0.00001287571,0.0004518559,0.0005734465,0.00001751353,0.00001685479,0.00002335234,0.0001372856,0.0001261796,0.000385462,0.9967512,0.001470735],"study_design_scores_gemma":[0.00008075342,0.000009272507,0.00215351,0.0001989574,0.0000153442,0.00004332824,0.00006740789,0.0001529288,0.0002026963,0.0007067976,0.9963516,0.00001727217],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004597478,0.00002878472,0.00003564204,0.00003215577,0.00001041595,0.000005134566,0.9989769,0.000313815,0.0005512364],"genre_scores_gemma":[0.0001443933,0.00003103734,0.0001463409,0.00003528754,0.00000301058,0.00003130339,0.9991641,0.00009060493,0.0003538987],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8711382,"threshold_uncertainty_score":0.4310856,"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."}}