{"id":"W6905957810","doi":"10.15468/dl.vrycxa","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Alien; Range (aeronautics); State (computer science)","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":[0.0008986343,0.002056378,0.001490269,0.00487332,0.0009487696,0.002384695,0.002629062,0.00189587,0.1617047],"category_scores_gemma":[0.005606388,0.0008886848,0.00121172,0.009511419,0.0004427481,0.00212229,0.002454579,0.001750857,0.2229574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425019,"about_ca_system_score_gemma":0.002197296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0205295,"about_ca_topic_score_gemma":0.03320798,"domain_scores_codex":[0.9990258,0.0001327248,0.0001210122,0.0003528925,0.0002013679,0.0001661615],"domain_scores_gemma":[0.9977618,0.0006336174,0.0002115301,0.0005820483,0.0005515224,0.0002594961],"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":[0.00003237817,0.00001182901,0.0004116993,0.0005347623,0.00001420121,0.00001478909,0.00002141435,0.0001363723,0.0001269556,0.0003431904,0.996799,0.001553434],"study_design_scores_gemma":[0.00007693395,0.00001086479,0.00195959,0.0001839914,0.00001484489,0.00003766395,0.00006846192,0.000158357,0.0001970009,0.0007746961,0.9964991,0.00001848732],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004989302,0.00002835871,0.00004122643,0.00003299401,0.00001293023,0.000005203496,0.9987838,0.0003967697,0.0006489312],"genre_scores_gemma":[0.0001655376,0.00003405155,0.0001908088,0.00004463399,0.000003694095,0.00004067081,0.9988971,0.0001493204,0.000474324],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8382953,"threshold_uncertainty_score":0.5409563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}