{"id":"W6906138252","doi":"10.15468/dl.w5chv9","title":"Occurrence Download","year":2015,"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); 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":[0.001055084,0.00194432,0.001639259,0.005361938,0.0009999326,0.002752318,0.003040061,0.002004391,0.1482911],"category_scores_gemma":[0.006024327,0.0009110989,0.001196339,0.01122365,0.0004241501,0.002420899,0.002643977,0.002080449,0.2088622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001688003,"about_ca_system_score_gemma":0.00256601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02344163,"about_ca_topic_score_gemma":0.0403,"domain_scores_codex":[0.9988704,0.0001491378,0.0001493405,0.0003844575,0.0002635978,0.0001830139],"domain_scores_gemma":[0.99754,0.0006497739,0.0002435428,0.0006737919,0.0006046252,0.0002883632],"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":[0.00002580727,0.00001084978,0.0003895523,0.0004850137,0.00001570217,0.00001370824,0.0000237889,0.0001174678,0.0001043739,0.0004398562,0.9969591,0.001414896],"study_design_scores_gemma":[0.00005869295,0.000006562865,0.001823237,0.0001786946,0.00001412145,0.00003312213,0.0000655025,0.0001321285,0.0001783675,0.0007639356,0.9967293,0.00001641578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004345759,0.00002937659,0.00005003183,0.00003398061,0.00001150801,0.00000488965,0.9987724,0.0003629762,0.0006912714],"genre_scores_gemma":[0.0001412051,0.00003189902,0.0001746002,0.00003562114,0.000002745974,0.00003284425,0.9990178,0.0001228875,0.0004402625],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8517089,"threshold_uncertainty_score":0.4960833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02668786630850237,"score_gpt":0.2410469455301918,"score_spread":0.2143590792216895,"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."}}