{"id":"W7138843418","doi":"10.5281/zenodo.19081137","title":"Open Data Initiatives and Governance Transparency in Tunisia: A Socio-Technical Perspective","year":2014,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Transparency (behavior); Open data; Open government; Usability; Corporate governance; Digital literacy; Government (linguistics); Qualitative property; Perspective (graphical)","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.007550856,0.000293041,0.000272234,0.002660555,0.004312885,0.007589474,0.0006524716,0.001110004,0.003576256],"category_scores_gemma":[0.009657329,0.0002588708,0.0003103734,0.005006147,0.005026191,0.004303991,0.0047653,0.001275853,0.0001599501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01372135,"about_ca_system_score_gemma":0.008800384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07077682,"about_ca_topic_score_gemma":0.05666569,"domain_scores_codex":[0.9931932,0.004545227,0.0002463264,0.000345955,0.0006096247,0.001059677],"domain_scores_gemma":[0.9903805,0.005778683,0.002295975,0.0003166244,0.0007379737,0.0004902773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002034158,0.0005525059,0.463021,0.0008763892,0.0001413791,0.00301421,0.2204396,0.00399898,0.001720724,0.216097,0.002667756,0.08726704],"study_design_scores_gemma":[0.00004411905,0.0002144677,0.3335921,0.001692811,0.00009861623,0.0005876311,0.5385903,0.009588885,0.001372532,0.03035614,0.08376696,0.00009543275],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603201,0.00160195,0.002838247,0.009864827,0.00003223889,0.0001040712,0.0002033594,0.00001263298,0.02502262],"genre_scores_gemma":[0.9979092,0.0004576414,0.0005451675,0.0002007216,0.00001232255,0.0000366803,0.00003109835,0.000002789315,0.0008043154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9956871,"threshold_uncertainty_score":0.1407297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08271824146301664,"score_gpt":0.3357100006266629,"score_spread":0.2529917591636462,"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."}}