{"id":"W4412146717","doi":"10.59490/dgo.2025.1068","title":"Leveraging AI Models for Automated Pattern Detection in Citizen Participation Data","year":2025,"lang":"en","type":"article","venue":"Conference on Digital Government Research","topic":"Computational and Text Analysis Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Rimouski","funders":"","keywords":"Computer science; Citizen science; Data science; Artificial intelligence","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":[0.004131394,0.0008238983,0.0007450808,0.003901306,0.0008359123,0.003334304,0.001571966,0.001117031,0.002723431],"category_scores_gemma":[0.02140931,0.0003934512,0.00142144,0.003002645,0.001025497,0.004255555,0.001333296,0.002038626,0.001371946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001781547,"about_ca_system_score_gemma":0.001876523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0122694,"about_ca_topic_score_gemma":0.01686838,"domain_scores_codex":[0.9972855,0.001050925,0.0002060062,0.0006684875,0.0006266374,0.0001623887],"domain_scores_gemma":[0.9815375,0.01462332,0.001033161,0.0009685124,0.001617117,0.0002203383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003867273,0.001003727,0.04661302,0.0005831511,0.0004036146,0.0004805835,0.001715285,0.4172862,0.0052855,0.05045333,0.01312821,0.4626607],"study_design_scores_gemma":[0.000005998642,0.00002327073,0.001108497,0.00002354109,0.00001322829,0.00003491146,0.0001090511,0.9757996,0.0004720267,0.02060251,0.001797211,0.00001013006],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07031407,0.0006640079,0.9118385,0.003800186,0.0001464018,0.0005169247,0.001496412,0.002586441,0.008637077],"genre_scores_gemma":[0.5938941,0.0006352268,0.3946876,0.0008605649,0.0002115928,0.0006904745,0.00335276,0.0001900878,0.005477551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0122694,"threshold_uncertainty_score":0.024396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3658016113982027,"score_gpt":0.5243350730544242,"score_spread":0.1585334616562215,"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."}}