{"id":"W6905872191","doi":"10.15468/dl.wqd4sa","title":"Occurrence Download","year":2021,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Herbarium; Download; Biodiversity; Barcode; Matching (statistics); DNA barcoding; Range (aeronautics)","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":[0.0009801848,0.002348152,0.001954247,0.006438566,0.001176443,0.003788496,0.002942322,0.002038223,0.2648162],"category_scores_gemma":[0.007171414,0.001011695,0.001752891,0.01126274,0.0003710123,0.00404836,0.004037964,0.001945327,0.363941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001544365,"about_ca_system_score_gemma":0.00208296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01712324,"about_ca_topic_score_gemma":0.03053705,"domain_scores_codex":[0.9986168,0.0001508866,0.0001913142,0.0005318109,0.0002954306,0.0002136844],"domain_scores_gemma":[0.9972626,0.0007153561,0.0002230993,0.0007232465,0.0007873959,0.0002882599],"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":[0.00004069396,0.00001171027,0.0004753018,0.0006664818,0.00001778449,0.00002038379,0.00002920556,0.0001111754,0.0001046484,0.0003927721,0.9949577,0.003172185],"study_design_scores_gemma":[0.00005295075,0.00001214299,0.00174019,0.0001938353,0.00001602011,0.00004949467,0.000111228,0.0002238255,0.000190142,0.001041278,0.9963476,0.000021288],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005381641,0.00004612737,0.0001111635,0.00004838678,0.00002258786,0.000008414105,0.9972336,0.001328578,0.001147392],"genre_scores_gemma":[0.000226753,0.00005634922,0.0004405509,0.00007054066,0.000007919886,0.00005313351,0.9976864,0.0004425783,0.001015744],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7351838,"threshold_uncertainty_score":0.8858985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878725496536469,"score_gpt":0.2292776369319846,"score_spread":0.2104903819666199,"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."}}