{"id":"W32949932","doi":"","title":"An agent-based domestic electricity consumption advisory system","year":2010,"lang":"en","type":"article","venue":"Research Repository UCD (University College Dublin)","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ninth; Electricity; Electricity system; Multi-agent system; Computer science; Autonomous agent; Energy consumption; Consumption (sociology); Engineering management; Advisory committee; Operations research; Environmental economics; Engineering; Electricity generation; Artificial intelligence; Electrical engineering; Management; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001882177,0.0001920692,0.0002496972,0.001003151,0.001603695,0.0002556956,0.001533485,0.0002543845,0.00001982654],"category_scores_gemma":[0.00008175918,0.0002171308,0.0001214366,0.00145322,0.000157315,0.001548267,0.000175223,0.0007719282,0.0001947058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005730892,"about_ca_system_score_gemma":0.0007099996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004699542,"about_ca_topic_score_gemma":0.0002076127,"domain_scores_codex":[0.9958994,0.001215782,0.0002570307,0.0007799602,0.001210233,0.0006375299],"domain_scores_gemma":[0.9970248,0.0003186684,0.0001750697,0.001199506,0.0007825231,0.0004994185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001353595,0.0004710135,0.0009883597,0.0002761288,0.00004211846,0.001212521,0.0002713732,0.0001191903,0.2790224,0.7149236,0.001836571,0.0007013608],"study_design_scores_gemma":[0.001203149,0.0002498134,0.01629332,0.00006136797,0.00001134528,0.00008998143,0.0002961934,0.9732752,0.005208726,0.0000140943,0.003022474,0.0002742616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9218534,0.00002721204,0.07520992,0.0001672005,0.0008271938,0.0006761167,0.00002285012,0.0004055583,0.0008105868],"genre_scores_gemma":[0.9939065,0.000002916766,0.002975496,0.00001312721,0.0001747507,0.000006695292,0.00001302288,0.00001475811,0.002892724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9731561,"threshold_uncertainty_score":0.9996961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03955747774284531,"score_gpt":0.3000690303417829,"score_spread":0.2605115525989376,"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."}}