{"id":"W4406069343","doi":"10.1016/j.envsoft.2025.106317","title":"OFPO &amp; KGFPO: Ontology and knowledge graph for flood process observation","year":2025,"lang":"en","type":"article","venue":"Environmental Modelling & Software","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Trudell Medical International; Military Health System; National Key Research and Development Program of China; China Scholarship Council; Ministry of Water Resources; Magee-Womens Research Institute; Natural Science Foundation of Hubei Province; National Natural Science Foundation of China; Rare Disease Foundation","keywords":"Ontology; Computer science; Graph; Flood myth; Knowledge graph; Process (computing); Knowledge management; Information retrieval; Theoretical computer science; Programming language; Geography; Epistemology; Philosophy; Archaeology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005426935,0.0006305565,0.0004945271,0.002393456,0.0008143655,0.00210032,0.001202023,0.001126711,0.009000137],"category_scores_gemma":[0.002707877,0.0005363337,0.00128577,0.001606591,0.000764052,0.004035411,0.00235701,0.001299151,0.002663609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064464,"about_ca_system_score_gemma":0.001949104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02566159,"about_ca_topic_score_gemma":0.03333553,"domain_scores_codex":[0.9996359,0.00005632789,0.00003998743,0.0000947988,0.0001317213,0.00004115703],"domain_scores_gemma":[0.9993098,0.0002312235,0.00006338274,0.0002411801,0.00008914061,0.00006528556],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004365695,0.0003763209,0.005828714,0.00159133,0.0002085357,0.001215926,0.001837177,0.05239249,0.01754162,0.3067544,0.1019396,0.5098773],"study_design_scores_gemma":[0.00007742457,0.00006757105,0.004143279,0.0003321361,0.0001448572,0.0008042614,0.0005139533,0.2900083,0.01543736,0.1984984,0.4898365,0.000135975],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007938267,0.000146268,0.9350266,0.0004863765,0.0001149507,0.0003400991,0.01839622,0.02659551,0.01095577],"genre_scores_gemma":[0.1669432,0.0008273278,0.7632162,0.0003763738,0.00005017088,0.0006619863,0.05055955,0.004963449,0.01240168],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02566159,"threshold_uncertainty_score":0.05102444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03008632792475968,"score_gpt":0.2694087393100672,"score_spread":0.2393224113853075,"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."}}