{"id":"W4361762344","doi":"10.1504/ijcc.2023.129773","title":"Legal issues of consumer privacy protection in the cloud computing environment: analytic study in GDPR, and USA legislations","year":2023,"lang":"en","type":"article","venue":"International Journal of Cloud Computing","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Cloud computing; Data Protection Act 1998; Information privacy; Service provider; Business; Privacy by Design; Privacy protection; Internet privacy; Computer security; Privacy law; Service (business); Data breach; Consumer protection; Privacy policy; Computer science; Law; Political science; Marketing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003815486,0.00009423565,0.0001999704,0.0004210437,0.0002127027,0.0001463746,0.0006434346,0.00005109802,0.00001304222],"category_scores_gemma":[0.0008651499,0.00008266233,0.00005735019,0.000465441,0.0001331273,0.0003244436,0.0002599486,0.0003817211,0.000005462027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001388748,"about_ca_system_score_gemma":0.00008829228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003815922,"about_ca_topic_score_gemma":0.0008434018,"domain_scores_codex":[0.9976103,0.0005889875,0.0006781996,0.0001577249,0.0007819583,0.0001828528],"domain_scores_gemma":[0.9988233,0.0003642857,0.0005246332,0.000120243,0.0001364419,0.00003103028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002623071,0.001391637,0.6809649,0.00004792092,0.0003475888,0.0002703639,0.2091998,0.01932984,0.0005852059,0.01616205,0.000605671,0.07083274],"study_design_scores_gemma":[0.003804775,0.0004599552,0.8386773,0.0006079016,0.00006389523,0.0001223297,0.04936253,0.06531414,0.0001384696,0.01765007,0.02338648,0.0004121217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933521,0.0001644511,0.002490167,0.002481465,0.0008141481,0.0003674841,0.000002946652,0.00001178704,0.0003154234],"genre_scores_gemma":[0.9987598,0.000127714,0.000254129,0.00003200888,0.0008007228,0.000001753953,0.00000195076,0.000005793096,0.00001610535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1598372,"threshold_uncertainty_score":0.5768558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05012244870645221,"score_gpt":0.3531606861904428,"score_spread":0.3030382374839906,"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."}}