{"id":"W6943629424","doi":"10.15468/dl.syh2ev","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Data access; Real world data","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":[0.0009078087,0.001946165,0.001514888,0.00443574,0.0009666138,0.00232783,0.002797698,0.002041711,0.1452604],"category_scores_gemma":[0.005295542,0.000892835,0.001162665,0.008847427,0.0004446571,0.002135375,0.002491577,0.001974742,0.2047035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001568565,"about_ca_system_score_gemma":0.002247711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0231775,"about_ca_topic_score_gemma":0.03974381,"domain_scores_codex":[0.9991197,0.0001155164,0.0001133112,0.0003063484,0.0001914242,0.0001538232],"domain_scores_gemma":[0.9979643,0.0005504038,0.0001933132,0.0005456725,0.0005006947,0.0002456018],"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":[0.00002855232,0.00001178198,0.0004121848,0.0005440627,0.00001545168,0.00001683577,0.00002803326,0.0001418239,0.0001392723,0.0004110846,0.9967995,0.001451479],"study_design_scores_gemma":[0.00006789259,0.000007557007,0.001849442,0.0001805533,0.00001386536,0.0000376555,0.00007717857,0.0001598608,0.0001964717,0.0007073397,0.9966851,0.0000170117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000453462,0.00002465715,0.00004706821,0.00003303486,0.00001221682,0.000005239996,0.9988052,0.0003888673,0.0006383883],"genre_scores_gemma":[0.0001610119,0.00002864663,0.0002050591,0.00004082023,0.000003046899,0.0000399511,0.9989784,0.0001411734,0.0004020035],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8547396,"threshold_uncertainty_score":0.4859444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}