{"id":"W2147383536","doi":"10.1007/s12394-010-0046-y","title":"SmartPrivacy for the Smart Grid: embedding privacy into the design of electricity conservation","year":2010,"lang":"en","type":"article","venue":"Identity in the Information Society","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"Privacy Analytics (Canada)","funders":"","keywords":"Smart grid; Computer security; Consumer privacy; Accountability; Transparency (behavior); Business; Internet privacy; Information privacy; Personally identifiable information; Environmental economics; Computer science; Economics; Engineering; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008801593,0.00009606532,0.000109782,0.00004269401,0.001813457,0.0004506924,0.001463236,0.000137573,0.00002786595],"category_scores_gemma":[0.004532112,0.0000579505,0.0001432261,0.0007684864,0.0003458049,0.003463177,0.0001834887,0.0004279881,0.00001509794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000095127,"about_ca_system_score_gemma":0.0002240566,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01164875,"about_ca_topic_score_gemma":0.00364319,"domain_scores_codex":[0.9983543,0.0002818848,0.0004428342,0.00009021196,0.0005955494,0.0002352587],"domain_scores_gemma":[0.99738,0.00142515,0.0003778682,0.0004838564,0.0003085812,0.00002451012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009625862,0.0001398259,0.009000673,0.0001431204,0.00009986026,1.071365e-7,0.7494352,0.0003595304,0.00120649,0.1124356,0.1098058,0.01727759],"study_design_scores_gemma":[0.00178794,0.000112878,0.05013817,0.00004286207,0.0001470303,0.000008328198,0.1081684,0.08585116,0.002025738,0.1771773,0.5740262,0.0005140316],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4377773,0.00009066306,0.5239673,0.03200842,0.001701495,0.003639473,0.00002994723,0.00008676575,0.0006987256],"genre_scores_gemma":[0.9940377,0.0003368081,0.003020376,0.001983145,0.0003356679,0.0002270403,0.00003150724,0.000004771068,0.00002293247],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6412668,"threshold_uncertainty_score":0.999486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03380659812308561,"score_gpt":0.3338378901018255,"score_spread":0.3000312919787398,"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."}}