{"id":"W6943418787","doi":"10.15468/dl.x454xf","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":"Download; Matching (statistics); Range (aeronautics); State (computer science); 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":[0.001112791,0.001984565,0.001612346,0.005268554,0.001054845,0.00265964,0.002916657,0.002033219,0.1628118],"category_scores_gemma":[0.006241851,0.0009617258,0.001140222,0.01016019,0.0004636087,0.002367726,0.002663109,0.002060654,0.2178056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001672322,"about_ca_system_score_gemma":0.002430398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02331471,"about_ca_topic_score_gemma":0.03832535,"domain_scores_codex":[0.9989016,0.0001457463,0.0001432433,0.0003722776,0.0002566811,0.0001803778],"domain_scores_gemma":[0.997393,0.0007528849,0.0002449094,0.000680264,0.0006356773,0.0002932683],"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":[0.00002847477,0.00001134202,0.0003747373,0.0005293433,0.00001461113,0.00001629335,0.00002700205,0.0001197995,0.000124522,0.0004202795,0.9969239,0.001409785],"study_design_scores_gemma":[0.00006536537,0.000007094893,0.001816563,0.0001867359,0.00001380969,0.00003907666,0.0000755928,0.0001345294,0.0001912694,0.0007320658,0.9967201,0.00001777092],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003911688,0.00002371129,0.00004938272,0.00003311528,0.00001113561,0.000005028891,0.9987923,0.0003852112,0.0006609592],"genre_scores_gemma":[0.0001510373,0.00002977929,0.0002030298,0.00003936486,0.000003006048,0.00003920455,0.9989339,0.0001634944,0.0004372018],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8371882,"threshold_uncertainty_score":0.5446598,"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."}}