{"id":"W7117726295","doi":"10.1145/3773274.3774662","title":"A Hybrid GraphRAG Framework for Geospatial Contextualization in Decision Support Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Contextualization; Geospatial analysis; Flexibility (engineering); Decision support system; Architecture; Graph; Knowledge representation and reasoning; Face (sociological concept); Bayesian network","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":[],"consensus_categories":[],"category_scores_codex":[0.0008445418,0.0005545037,0.000534283,0.001394517,0.0005089905,0.001588168,0.001461563,0.0008798749,0.003680976],"category_scores_gemma":[0.002167039,0.0003144128,0.0009969216,0.001396192,0.0007027816,0.002872185,0.001570047,0.001024894,0.001009278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008620178,"about_ca_system_score_gemma":0.001205382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01554616,"about_ca_topic_score_gemma":0.02155164,"domain_scores_codex":[0.9993969,0.000248424,0.00004211927,0.0001586882,0.0001165884,0.00003716456],"domain_scores_gemma":[0.9995176,0.0002149981,0.00003343337,0.0001236195,0.00008091451,0.00002944099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001452361,0.0001785668,0.001001833,0.0004108078,0.0001379313,0.0003361491,0.0005370142,0.4989295,0.006847893,0.2039808,0.01110506,0.2763891],"study_design_scores_gemma":[0.00001597898,0.00003171972,0.0001598177,0.00003187458,0.00003213343,0.00005028233,0.00006201045,0.8720642,0.001590735,0.1130772,0.01286696,0.0000171413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005492311,0.0004305807,0.9880934,0.0003847188,0.00002730742,0.00005663675,0.0004663876,0.003382332,0.001666398],"genre_scores_gemma":[0.2303697,0.0006032204,0.7641368,0.0003103428,0.00004870117,0.0001536031,0.001680578,0.0003541815,0.002342978],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01554616,"threshold_uncertainty_score":0.03091139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01507168494380559,"score_gpt":0.3036364563265237,"score_spread":0.2885647713827181,"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."}}