{"id":"W6905876025","doi":"10.15468/dl.pmz8cq","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":[0.0008987392,0.002056775,0.001502066,0.00484595,0.0009617699,0.002388396,0.002582885,0.001938273,0.1621579],"category_scores_gemma":[0.005472014,0.0008745622,0.001184877,0.009415129,0.0004453432,0.002053419,0.002454809,0.001763127,0.2212545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444521,"about_ca_system_score_gemma":0.002243546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02058987,"about_ca_topic_score_gemma":0.03309054,"domain_scores_codex":[0.9990361,0.0001309753,0.0001199181,0.0003474173,0.0002008952,0.0001646923],"domain_scores_gemma":[0.9977713,0.0006387824,0.0002153511,0.0005634404,0.0005571445,0.0002539742],"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":[0.0000327033,0.00001211254,0.0004182955,0.0005471606,0.00001418257,0.00001503195,0.00002249144,0.0001339457,0.0001338551,0.0003427174,0.9968035,0.001524083],"study_design_scores_gemma":[0.00008006259,0.00001109109,0.001981927,0.0001874759,0.00001542422,0.00003801655,0.00007078097,0.0001608668,0.0002090683,0.0007661529,0.9964599,0.00001919003],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004903077,0.00002736218,0.00003972019,0.00003248156,0.00001248318,0.000005283202,0.9988305,0.0003695378,0.0006335524],"genre_scores_gemma":[0.0001673545,0.00003334851,0.0001933888,0.0000445765,0.000003668664,0.00004355784,0.9988937,0.0001431825,0.0004772811],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.837842,"threshold_uncertainty_score":0.5424724,"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."}}