{"id":"W2111317698","doi":"10.1002/meet.2011.14504801086","title":"Seeking information from government resources: A comparative analysis of two communities' Web searching of municipal government Web sites","year":2011,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"World Wide Web; Government (linguistics); Sample (material); Computer science; Web standards; Nonprobability sampling; Internet privacy; The Internet; Sociology; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005537827,0.0003586503,0.0009261404,0.01103812,0.003898073,0.004039583,0.001209618,0.00135137,0.002491513],"category_scores_gemma":[0.03416209,0.000458595,0.0008290459,0.01020915,0.003300434,0.005426094,0.005054461,0.001087614,0.0004320299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004703323,"about_ca_system_score_gemma":0.003240291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09951834,"about_ca_topic_score_gemma":0.1819038,"domain_scores_codex":[0.9936824,0.003045466,0.0003739705,0.0006089074,0.001428118,0.0008612008],"domain_scores_gemma":[0.9726487,0.01522649,0.003936645,0.0009598996,0.00487355,0.002354631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001183699,0.0008898312,0.531826,0.0006809033,0.0003144235,0.0009707656,0.4372126,0.0001376719,0.00154526,0.001465532,0.0009520905,0.02282125],"study_design_scores_gemma":[0.00003769274,0.0003749346,0.6023089,0.0001214869,0.00009859853,0.0002130972,0.3943983,0.0005632812,0.0001787842,0.0002723278,0.001392544,0.00004005444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985024,0.0001319901,0.00007970142,0.00004881939,0.000002477842,0.00004557172,0.00009079197,0.000002952179,0.001095304],"genre_scores_gemma":[0.9989202,0.0001247995,0.0002533475,0.00004311916,0.000004798027,0.00007543006,0.0002485315,0.000008075229,0.0003217816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09951834,"threshold_uncertainty_score":0.1978782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03797773708875888,"score_gpt":0.3040543642564015,"score_spread":0.2660766271676426,"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."}}