{"id":"W2749155099","doi":"10.1109/fuzz-ieee.2017.8015650","title":"A graph-based semi-supervised learning approach towards household energy disaggregation","year":2017,"lang":"en","type":"article","venue":"","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Graph; Machine learning; Artificial intelligence; Theoretical computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.001455586,0.001019603,0.001848098,0.001426958,0.0006376557,0.000875418,0.002405263,0.001265747,0.001387075],"category_scores_gemma":[0.003718095,0.0006010085,0.00108571,0.00182488,0.0008195857,0.001391177,0.001255202,0.00171484,0.000690684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009344398,"about_ca_system_score_gemma":0.001128357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00646844,"about_ca_topic_score_gemma":0.01037079,"domain_scores_codex":[0.9984106,0.0006461618,0.00007162575,0.000485617,0.0002810143,0.0001049305],"domain_scores_gemma":[0.9967837,0.001653455,0.0003987518,0.0005176954,0.0005277316,0.000118663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001952698,0.0003314899,0.002624935,0.0001731255,0.0001752107,0.0001491825,0.0002566768,0.7460268,0.00300344,0.01005905,0.007706285,0.2292985],"study_design_scores_gemma":[0.000003102999,0.000007710217,0.000102918,0.000002275602,0.00000345889,0.000007859618,0.000005512992,0.9952803,0.00019047,0.004138084,0.0002552049,0.000003101676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01380396,0.0002198261,0.9834086,0.0002142442,0.00003056293,0.00005261477,0.000225403,0.001252222,0.0007926086],"genre_scores_gemma":[0.6150718,0.0002379014,0.3771734,0.0003856248,0.0001892761,0.0002620458,0.002178727,0.0002736678,0.004227633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00646844,"threshold_uncertainty_score":0.01286161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02068160592917669,"score_gpt":0.1991166588901605,"score_spread":0.1784350529609838,"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."}}