{"id":"W6887198348","doi":"10.15468/dl.vt538s","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":[0.0009032075,0.001987974,0.001464772,0.004654688,0.0009470257,0.002401532,0.002602756,0.001873755,0.1675974],"category_scores_gemma":[0.00572966,0.0009055449,0.001180647,0.009399802,0.0004318661,0.002167994,0.002481385,0.001809112,0.2220213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00142707,"about_ca_system_score_gemma":0.002231922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01998236,"about_ca_topic_score_gemma":0.03263997,"domain_scores_codex":[0.9990268,0.0001310882,0.0001211019,0.0003547817,0.0001996504,0.0001665842],"domain_scores_gemma":[0.9977005,0.0006619714,0.0002189318,0.0005993462,0.0005568229,0.0002624189],"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":[0.00003190951,0.00001139009,0.0003923754,0.0005055175,0.00001397789,0.00001407079,0.00002101811,0.0001332912,0.0001254012,0.0003645677,0.9969029,0.001483518],"study_design_scores_gemma":[0.00007572382,0.00001020832,0.001868095,0.0001757918,0.00001473759,0.00003616595,0.00006626395,0.0001557003,0.000200661,0.0008058042,0.9965725,0.00001829185],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004787839,0.000024894,0.00004318207,0.0000329488,0.00001261627,0.000004977594,0.9988018,0.000382395,0.0006492666],"genre_scores_gemma":[0.0001662078,0.00003264276,0.0001986843,0.00004654686,0.000003597351,0.0000416852,0.9988534,0.0001593974,0.000497755],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8324026,"threshold_uncertainty_score":0.5606691,"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."}}