{"id":"W6887146869","doi":"10.15468/dl.r2fq7k","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); Alien; 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":[0.001029753,0.001845582,0.001569528,0.005243704,0.001102527,0.00268436,0.002870159,0.002151254,0.1645393],"category_scores_gemma":[0.006290364,0.0008996744,0.00126368,0.01008374,0.0004619434,0.002567806,0.002736524,0.002038248,0.2350923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001700353,"about_ca_system_score_gemma":0.002467732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02351744,"about_ca_topic_score_gemma":0.03836774,"domain_scores_codex":[0.9988701,0.000153381,0.0001445952,0.0003906846,0.0002529049,0.0001883938],"domain_scores_gemma":[0.9972515,0.000766275,0.0002373748,0.0007280174,0.0007245681,0.0002922964],"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":[0.00002751184,0.00001152478,0.0003644725,0.0005381281,0.0000131848,0.00001518632,0.00002478467,0.0001056346,0.000117883,0.0003900407,0.9969534,0.001438255],"study_design_scores_gemma":[0.00005730899,0.000007851462,0.001817547,0.0001965379,0.00001259341,0.00003461933,0.00008171423,0.0001204233,0.0001718484,0.0006868486,0.9967957,0.00001695175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004313745,0.0000278902,0.00004478161,0.00004194948,0.00001368563,0.00000601014,0.9987324,0.0003637882,0.0007263797],"genre_scores_gemma":[0.0001539092,0.00003566747,0.00019665,0.00004780228,0.000003719834,0.00004304251,0.9988616,0.0001400445,0.0005175671],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8354607,"threshold_uncertainty_score":0.5504388,"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."}}