{"id":"W4383098061","doi":"10.2196/48645","title":"Comprehensive Ontology of Fibroproliferative Diseases: Protocol for a Semantic Technology Study","year":2023,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Ontology; Computer science; Protocol (science); Natural language processing; Data science; Medicine; Information retrieval; Pathology; Alternative medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000534655,0.0001869381,0.0003672959,0.0003745768,0.0001959817,0.0000252225,0.0005733029,0.0003054017,0.00001910099],"category_scores_gemma":[0.0007359951,0.0001475616,0.0001013723,0.0008279495,0.0008204505,0.000003635817,0.000543344,0.0002642418,0.00002654924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001830915,"about_ca_system_score_gemma":0.0002939971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007071026,"about_ca_topic_score_gemma":0.0000162234,"domain_scores_codex":[0.997562,0.0004062752,0.0003826671,0.0005964454,0.0003906368,0.0006619651],"domain_scores_gemma":[0.9982706,0.0001818598,0.0001129331,0.0006310338,0.0006857899,0.0001178169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01760476,0.01101661,0.1418765,0.008591196,0.000856564,0.0001805556,0.001869511,0.00003211072,0.4477599,0.00138926,0.2727775,0.09604561],"study_design_scores_gemma":[0.01124801,0.03672273,0.0166003,0.000748246,0.000006980644,0.00001364242,0.004197712,0.0001759682,0.05026735,0.003398268,0.8762004,0.0004203295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.0153905,0.00000332014,0.0001858203,0.0004665212,0.000005860695,0.983715,0.00004679156,0.0001017683,0.00008439813],"genre_scores_gemma":[0.01413329,2.264964e-7,0.0005080148,0.00002020623,0.0001059431,0.9846025,0.00002893106,0.0000283914,0.0005725498],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.603423,"threshold_uncertainty_score":0.6017388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3056264003572566,"score_gpt":0.5911879511506735,"score_spread":0.2855615507934169,"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."}}