{"id":"W6924656190","doi":"10.15468/dl.kthxp5","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":"Download; Matching (statistics); Range (aeronautics); Arctic; Data set","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":[0.001023164,0.002013025,0.001586232,0.005402415,0.0009279427,0.002499632,0.002738245,0.001829868,0.1802378],"category_scores_gemma":[0.005888143,0.0009388577,0.001215953,0.01032437,0.0004284606,0.002288569,0.002825101,0.001938691,0.2465089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527493,"about_ca_system_score_gemma":0.002528506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02350019,"about_ca_topic_score_gemma":0.03978494,"domain_scores_codex":[0.9988843,0.0001444039,0.0001446385,0.0003768908,0.0002586072,0.000191163],"domain_scores_gemma":[0.9973411,0.0006712834,0.0002457004,0.0006869875,0.0007287362,0.0003261621],"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":[0.00002972004,0.000009556065,0.0003276385,0.0005306747,0.00001506635,0.0000130525,0.00002000253,0.0001056398,0.0001240264,0.0003369028,0.997086,0.001401908],"study_design_scores_gemma":[0.00006601216,0.000007554151,0.00175584,0.0001842415,0.00001405783,0.00003033817,0.00005765139,0.0001075366,0.0001901944,0.0006598196,0.99691,0.00001674324],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003372516,0.00002221055,0.00004002617,0.00002870213,0.00001081188,0.000005232327,0.9988617,0.0003603119,0.0006374021],"genre_scores_gemma":[0.0001391814,0.0000318454,0.0001758946,0.00004241458,0.000003395048,0.00003836668,0.9989541,0.0001556265,0.0004591843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8197622,"threshold_uncertainty_score":0.6029555,"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."}}