{"id":"W6887385732","doi":"10.15468/dl.zq5txj","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); UniProt","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":[0.0009595252,0.002000167,0.001570044,0.004750342,0.0009855255,0.002361804,0.002800996,0.002063477,0.1316691],"category_scores_gemma":[0.005416946,0.0008850616,0.001226462,0.009521856,0.0004457949,0.002107517,0.002437544,0.002004806,0.1869375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649796,"about_ca_system_score_gemma":0.002314359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02384811,"about_ca_topic_score_gemma":0.03836609,"domain_scores_codex":[0.9990224,0.0001311473,0.0001275641,0.0003290169,0.0002200927,0.0001698776],"domain_scores_gemma":[0.9978789,0.0005932804,0.0002038396,0.0005607987,0.0005150652,0.0002480315],"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":[0.00003277651,0.00001307429,0.0004363625,0.0005765446,0.0000163712,0.00001735822,0.0000274226,0.0001596605,0.0001459716,0.0004152566,0.9965733,0.00158593],"study_design_scores_gemma":[0.00007410558,0.000008463264,0.002015521,0.0001977165,0.00001478094,0.0000411733,0.00008180647,0.0001803544,0.0002149918,0.0007269384,0.9964259,0.00001823373],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004878372,0.00002799021,0.00004548227,0.00003430348,0.00001175611,0.00000524595,0.9988669,0.0003781,0.0005813786],"genre_scores_gemma":[0.0001595121,0.0000315927,0.0001949447,0.00003802779,0.000002788969,0.00003663178,0.9990349,0.0001273807,0.0003742415],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8683308,"threshold_uncertainty_score":0.4404772,"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."}}