{"id":"W6943344373","doi":"10.15468/dl.xxu889","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); Alien; Range (aeronautics); Data collection","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":[0.001062296,0.00188388,0.001619925,0.005029323,0.0009770739,0.00260854,0.002834669,0.002071416,0.1672139],"category_scores_gemma":[0.006198484,0.0009024927,0.00118062,0.01004391,0.0004458848,0.002295753,0.002430738,0.001995684,0.2278058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001675047,"about_ca_system_score_gemma":0.002405101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02266162,"about_ca_topic_score_gemma":0.03524208,"domain_scores_codex":[0.9989461,0.0001460539,0.0001336995,0.0003587592,0.0002385466,0.0001768518],"domain_scores_gemma":[0.9974177,0.000755039,0.0002495895,0.0006567299,0.0006332204,0.0002876637],"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":[0.0000285368,0.00001094977,0.0003442827,0.0005392268,0.00001503188,0.00001354406,0.00002198754,0.0001228939,0.0001135923,0.0003826193,0.9970387,0.001368657],"study_design_scores_gemma":[0.00006871014,0.000007712674,0.001813667,0.0001951234,0.00001438567,0.00003193942,0.00006672305,0.0001330178,0.0001880723,0.0007684849,0.9966949,0.00001713719],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003511476,0.00002504759,0.00003906895,0.000033419,0.00001038104,0.000004852391,0.9989184,0.0003126355,0.0006211635],"genre_scores_gemma":[0.000152763,0.00003311731,0.0001736022,0.00004284869,0.000003301374,0.00004177897,0.9989459,0.0001369954,0.0004697623],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8327861,"threshold_uncertainty_score":0.5593864,"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."}}