{"id":"W6920927648","doi":"10.6084/m9.figshare.27246017.v1","title":"Additional file 1 of Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Applications of artificial intelligence; Key (lock); Ontology; Field (mathematics); Expert system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001682742,0.001337114,0.001086251,0.002576618,0.0007824234,0.002502736,0.00212461,0.001429762,0.796424],"category_scores_gemma":[0.02084576,0.0006832656,0.0009709775,0.003387949,0.0003595789,0.001716839,0.001801495,0.001256539,0.2593513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009849994,"about_ca_system_score_gemma":0.001493606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004239139,"about_ca_topic_score_gemma":0.00848256,"domain_scores_codex":[0.9992377,0.00015209,0.00009915171,0.0002288228,0.000199343,0.00008308718],"domain_scores_gemma":[0.9865726,0.0104219,0.000320906,0.0009652294,0.001329996,0.0003892897],"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":[0.0002269615,0.00005721486,0.000636445,0.001434284,0.00004064518,0.00006389545,0.00004288441,0.000478264,0.0002256962,0.0007515851,0.9871966,0.008845637],"study_design_scores_gemma":[0.002052735,0.000159636,0.007031918,0.0009737337,0.0001495196,0.0003746158,0.0002300836,0.004505697,0.002781894,0.01425599,0.9673316,0.0001526387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.000172536,0.00002165895,0.0008603813,0.00007746719,0.00004617037,0.00004740567,0.9953049,0.002404659,0.001064798],"genre_scores_gemma":[0.003833734,0.0000789515,0.008700819,0.0002651369,0.000052195,0.0006604935,0.9788414,0.002988187,0.004579125],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.796424,"threshold_uncertainty_score":0.2903765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08765391331783524,"score_gpt":0.3300715407708175,"score_spread":0.2424176274529822,"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."}}