{"id":"W6962105353","doi":"10.15468/dl.tdanz3","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Identification (biology); Sequence (biology)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000239176,0.0002793291,0.0002404157,0.00007317606,0.0001935807,0.00007386356,0.0005105271,0.0004935142,0.0001615349],"category_scores_gemma":[0.0001071235,0.0003025188,0.0002579126,0.0003452705,0.0001336836,0.00001882554,0.0005098125,0.0001432544,0.2132616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009465237,"about_ca_system_score_gemma":0.000148035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002226096,"about_ca_topic_score_gemma":0.00006120878,"domain_scores_codex":[0.9986423,0.00006669328,0.0003269332,0.0003107233,0.0003520676,0.0003012538],"domain_scores_gemma":[0.9986548,0.000004530224,0.0002451107,0.0007266179,0.0002211838,0.0001477226],"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":[0.00003449573,0.00001539206,0.0008431029,0.00006369869,0.0001157139,0.000001205535,0.000003610046,0.0001560556,0.000002075195,9.257755e-9,0.9983139,0.0004507491],"study_design_scores_gemma":[0.0002081702,0.00004187566,0.0001625675,0.000001375392,0.00009418066,0.000003010841,0.00004145116,2.940191e-7,0.00003377764,3.002002e-7,0.999119,0.0002939967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002701864,0.00005225248,0.000007057431,0.00005602848,0.0004139119,0.0001801018,0.9965199,0.00004437433,0.00002449835],"genre_scores_gemma":[0.00003773332,0.0002302067,0.000001160475,0.0002388629,0.000006625186,0.000004533011,0.9994799,3.344949e-8,8.718897e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2131001,"threshold_uncertainty_score":0.9999427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01064336769704338,"score_gpt":0.2170861724700051,"score_spread":0.2064428047729617,"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."}}