{"id":"W2978558391","doi":"10.5430/air.v8n2p1","title":"Use of a text mining method for classifying citizen report data and analyzing the occurrence trend of local problems","year":2019,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Safety Warnings and Signage","field":"Psychology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prioritization; Data collection; Transport engineering; Task (project management); Business; Computer science; Environmental planning; Geography; Engineering; Process management; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00198872,0.0007346236,0.000575718,0.009980196,0.0006860881,0.001491835,0.0006420136,0.0005862684,0.0009659667],"category_scores_gemma":[0.006254404,0.0001760659,0.000755614,0.007797023,0.0002605208,0.001093838,0.0003703981,0.0005945383,0.0007915032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005674566,"about_ca_system_score_gemma":0.0009874057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005500352,"about_ca_topic_score_gemma":0.006528125,"domain_scores_codex":[0.9980732,0.0003351286,0.0005004926,0.0004673417,0.0005321678,0.00009155775],"domain_scores_gemma":[0.9928092,0.00332407,0.001055342,0.0004174222,0.002211177,0.0001828423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005029365,0.001387294,0.1974727,0.001002596,0.0002572304,0.001418287,0.003069921,0.004396652,0.03214807,0.001503143,0.01172362,0.7451175],"study_design_scores_gemma":[0.0001674732,0.001310075,0.5494498,0.0004194334,0.0006259895,0.002633635,0.0101269,0.3156073,0.06330416,0.005747586,0.05031588,0.0002918213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.686205,0.0006707703,0.2649513,0.001364565,0.0004535493,0.003006002,0.02810275,0.004656593,0.01058955],"genre_scores_gemma":[0.6214189,0.00046101,0.3528504,0.0001755839,0.0001916514,0.001954911,0.01894182,0.0000909409,0.00391479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009980196,"threshold_uncertainty_score":0.01093668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.560830461341556,"score_gpt":0.5316667656691771,"score_spread":0.02916369567237886,"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."}}