{"id":"W6924691724","doi":"10.15468/dl.rx2f8s","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Alien; Range (aeronautics); State (computer science)","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":[0.0009420162,0.002024665,0.001470114,0.004309095,0.0009450017,0.002459159,0.002598245,0.002035473,0.1362236],"category_scores_gemma":[0.00596575,0.0008592693,0.001233417,0.008363985,0.0004341197,0.0019098,0.002193668,0.001866812,0.1887792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596678,"about_ca_system_score_gemma":0.002373165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02237033,"about_ca_topic_score_gemma":0.03609835,"domain_scores_codex":[0.9990196,0.000146518,0.0001249898,0.0003547685,0.0002011874,0.0001529215],"domain_scores_gemma":[0.9977787,0.0007220667,0.0002094428,0.000509431,0.0005437863,0.0002365683],"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":[0.00003528411,0.00001249877,0.0005244591,0.000590807,0.00001694223,0.00001784175,0.00002217674,0.0001689936,0.0001168815,0.0003988613,0.9965693,0.001525933],"study_design_scores_gemma":[0.00008617638,0.00001038572,0.00202415,0.0002102347,0.00001681739,0.00004197879,0.00006616925,0.0002001266,0.0001931901,0.000949582,0.9961815,0.00001979442],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004521782,0.00003162655,0.00004188251,0.00003728392,0.00001110413,0.000005122719,0.9988721,0.0003569318,0.0005986876],"genre_scores_gemma":[0.0001813141,0.00004005347,0.0002067156,0.00005271671,0.000003719681,0.00004284437,0.9988833,0.0001298357,0.0004595274],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8637763,"threshold_uncertainty_score":0.4557135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799640330987559,"score_gpt":0.2372738748553303,"score_spread":0.2192774715454547,"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."}}