{"id":"W2417732261","doi":"10.17645/up.v1i2.621","title":"Characterizing New Channels of Communication: A Case Study of Municipal 311 Requests in Edmonton, Canada","year":2016,"lang":"en","type":"article","venue":"Urban Planning","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Social Sciences and Humanities Research Council of Canada; University of Waterloo","keywords":"The Internet; Channel (broadcasting); Telecommunications; Government (linguistics); Service (business); World Wide Web; Computer science; Internet access; Business; Internet privacy; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.002134939,0.0005702779,0.0005620602,0.00340083,0.01902525,0.004417409,0.002483773,0.001732457,0.0024863],"category_scores_gemma":[0.006290319,0.0006399503,0.0004483274,0.009981897,0.004930881,0.001563467,0.004121161,0.001981262,0.0002575746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0764539,"about_ca_system_score_gemma":0.07992872,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9913881,"about_ca_topic_score_gemma":0.9980636,"domain_scores_codex":[0.995733,0.000855592,0.0001354056,0.0003012829,0.001003329,0.001971364],"domain_scores_gemma":[0.9929597,0.002408598,0.0007770951,0.0003411632,0.002308699,0.001204769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001302635,0.0003002611,0.2325408,0.0002952567,0.00004989052,0.01506352,0.7019862,0.001144849,0.001784194,0.006371466,0.004456813,0.03587644],"study_design_scores_gemma":[0.000006517179,0.00004181471,0.1253634,0.0001354984,0.00002338254,0.000944571,0.8540964,0.001165764,0.0004562321,0.0002609084,0.01744432,0.00006124125],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918935,0.000277919,0.0004262103,0.0007600571,0.00001014448,0.000151777,0.0003752302,0.00001110035,0.006093983],"genre_scores_gemma":[0.9916072,0.0006198809,0.001059351,0.000296301,0.000007417276,0.00007919635,0.0002831568,0.00001940842,0.006028021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0764539,"threshold_uncertainty_score":0.5547144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05004431807284802,"score_gpt":0.3110940005719885,"score_spread":0.2610496824991405,"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."}}