{"id":"W6924615914","doi":"10.15468/dl.nydtc2","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Data set; Set (abstract data type)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000754735,0.0004556112,0.0004449313,0.0001858385,0.000695208,0.0005288418,0.003788645,0.0002983916,0.01476392],"category_scores_gemma":[0.0002185951,0.0004994276,0.0002840978,0.001066339,0.000194021,0.002390584,0.004711061,0.0006497472,0.05776852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001044947,"about_ca_system_score_gemma":0.000410905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006619665,"about_ca_topic_score_gemma":0.00001311802,"domain_scores_codex":[0.9966893,0.0002408555,0.0006416421,0.0006336821,0.001256366,0.0005381354],"domain_scores_gemma":[0.9970335,0.00007358807,0.0004830775,0.001805218,0.0003390704,0.0002655023],"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":[0.00001251315,0.00008681106,0.0002759229,0.00009757036,0.00002454372,0.000007678975,0.0000836837,0.0001033998,9.691131e-9,0.000001786863,0.9910684,0.008237676],"study_design_scores_gemma":[0.0003151344,0.00009069377,0.0001147331,9.24326e-7,0.00002169774,0.00002094548,0.00005348405,0.00001651477,8.25366e-7,0.00001712875,0.9988549,0.0004930682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005927811,0.00003145419,0.001549637,0.0003855597,0.002104616,0.0005127903,0.994867,0.0003780333,0.0001115994],"genre_scores_gemma":[0.000005016755,0.00003150002,0.00006829988,0.0008050198,0.000002254817,0.00001202469,0.9990757,1.840262e-8,1.266694e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0430046,"threshold_uncertainty_score":0.9997457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01648800682483591,"score_gpt":0.2178908363310797,"score_spread":0.2014028295062438,"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."}}