{"id":"W4231634692","doi":"10.22215/etd/2011-09503","title":"Coming to terms with information and communications technologies : the role of the chief information officer of the government of Canada","year":2011,"lang":"en","type":"dissertation","venue":"","topic":"Knowledge Management and Technology","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; Library and Archives Canada","funders":"Social Sciences and Humanities Research Council of Canada; Public Works and Government Services Canada; University of Toronto; University of Oxford; Accenture","keywords":"Officer; Government (linguistics); Political science; The Internet; Library science; Telecommunications; Engineering; Computer science; World Wide Web; Law; Philosophy","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":[0.002500848,0.0003099632,0.0003285577,0.001404812,0.01744361,0.009098398,0.0008636737,0.001972752,0.01895064],"category_scores_gemma":[0.006715161,0.0003016795,0.0001527511,0.00288483,0.003004854,0.002426975,0.00124028,0.002896621,0.003127694],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09578404,"about_ca_system_score_gemma":0.4137584,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905323,"about_ca_topic_score_gemma":0.9971952,"domain_scores_codex":[0.9965294,0.000203134,0.0000770011,0.0002403557,0.001818334,0.00113185],"domain_scores_gemma":[0.9871356,0.0005576504,0.0002290813,0.0001078514,0.007235546,0.004734257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003253413,0.00005740389,0.007511052,0.0001753677,0.000009112721,0.0001868838,0.008845896,0.0002964704,0.0005037306,0.0294807,0.8614758,0.09142493],"study_design_scores_gemma":[0.000007230843,0.00001450437,0.01905056,0.000447414,0.00001297092,0.00005450295,0.02325957,0.0003003383,0.0004297948,0.002179605,0.954208,0.00003537751],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03655932,0.02223411,0.00109221,0.4930089,0.003274171,0.0002495984,0.003179585,0.0001225586,0.4402797],"genre_scores_gemma":[0.2330322,0.03862119,0.002305702,0.01184808,0.0003988928,0.0000525576,0.001071518,0.00009979284,0.7125701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9042159,"threshold_uncertainty_score":0.6949651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01410665127554623,"score_gpt":0.2427659808415745,"score_spread":0.2286593295660283,"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."}}