{"id":"W6886953367","doi":"10.15468/dl.k624ve","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":[0.0008946374,0.001872557,0.001490088,0.004861882,0.0009557337,0.002536367,0.002648647,0.001870166,0.181912],"category_scores_gemma":[0.006113401,0.0008846266,0.001150291,0.009525265,0.0004180446,0.002299391,0.002553758,0.001870448,0.2378514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519735,"about_ca_system_score_gemma":0.002244717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01926473,"about_ca_topic_score_gemma":0.03238585,"domain_scores_codex":[0.9989706,0.0001397077,0.0001315984,0.0003772082,0.0002112263,0.000169595],"domain_scores_gemma":[0.9976611,0.0006718088,0.0002213038,0.0005867751,0.0006026241,0.0002563641],"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":[0.00002712251,0.00001036068,0.0003628436,0.0005208792,0.00001259169,0.00001320708,0.00002036387,0.0001055639,0.0001078892,0.0003437324,0.9969918,0.001483726],"study_design_scores_gemma":[0.00006158931,0.000008790032,0.001760858,0.0001891985,0.00001325687,0.00003407732,0.00006577878,0.0001339726,0.0001768182,0.0007164086,0.996822,0.00001717118],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004207651,0.00002680114,0.00004288848,0.00003557561,0.00001279466,0.000005374587,0.9987842,0.0003608314,0.0006894137],"genre_scores_gemma":[0.0001615498,0.00003653479,0.0001984307,0.00004979528,0.000003908325,0.00004761401,0.9987596,0.0001621827,0.0005803207],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8180879,"threshold_uncertainty_score":0.6085564,"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."}}