{"id":"W6887175881","doi":"10.15468/dl.t959f3","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":[0.0009145295,0.002046444,0.001495898,0.004897609,0.0009589188,0.002394444,0.002573864,0.001936868,0.1590829],"category_scores_gemma":[0.005778432,0.0008806264,0.001199614,0.009655706,0.0004479222,0.002050387,0.002481555,0.001750322,0.2187451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001432327,"about_ca_system_score_gemma":0.002262994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02096352,"about_ca_topic_score_gemma":0.03366158,"domain_scores_codex":[0.9989949,0.000136496,0.0001280791,0.0003598575,0.0002096299,0.0001711903],"domain_scores_gemma":[0.9976723,0.0006655757,0.0002246201,0.0005900169,0.0005829037,0.0002645837],"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":[0.00003355234,0.00001250064,0.0004418073,0.0005549525,0.00001441277,0.00001525533,0.00002277683,0.0001362193,0.0001322732,0.000350482,0.9967499,0.001535935],"study_design_scores_gemma":[0.00008070699,0.00001139573,0.002063096,0.0001899336,0.00001555347,0.00003829575,0.00007261775,0.0001642336,0.0002059934,0.0007893631,0.9963495,0.0000193713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005047184,0.00002736838,0.00003996008,0.00003317612,0.00001259651,0.000005285932,0.9988177,0.000379627,0.0006337609],"genre_scores_gemma":[0.0001725079,0.00003331152,0.0001949431,0.00004606292,0.000003688263,0.00004273369,0.9988926,0.0001448895,0.0004693673],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8409171,"threshold_uncertainty_score":0.5321853,"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."}}