{"id":"W3167076394","doi":"10.82308/39049","title":"Quantification of ancillary service provision by microgrid","year":2016,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Service (business); Business; Computer science; Marketing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005676321,0.0007783523,0.0004699807,0.0007799493,0.0002842408,0.0009922335,0.0004899762,0.0004262827,0.002584784],"category_scores_gemma":[0.0016026,0.0002471278,0.0004162714,0.00134981,0.0002537634,0.0008016927,0.0004550451,0.0003081562,0.0003615332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008914,"about_ca_system_score_gemma":0.0006742169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01441664,"about_ca_topic_score_gemma":0.01010193,"domain_scores_codex":[0.9996523,0.00008370419,0.00001851083,0.00007167066,0.0001202003,0.00005370362],"domain_scores_gemma":[0.9994251,0.0002757144,0.00006868154,0.00006586898,0.0001398269,0.00002486119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000226614,0.00003831153,0.01034257,0.0001708049,0.00006214898,0.0001093611,0.00006142891,0.9449228,0.00876666,0.002312415,0.0007691374,0.03221774],"study_design_scores_gemma":[0.000008815525,0.0001102491,0.01091971,0.000018332,0.00002953779,0.00003689939,0.000116396,0.9805069,0.005115229,0.001332794,0.001787533,0.00001769305],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8747883,0.0006688578,0.1028927,0.0002702858,0.00006036887,0.000110998,0.002701377,0.00122227,0.01728484],"genre_scores_gemma":[0.9919268,0.0001341073,0.005887697,0.0000104357,0.000004739181,0.00002604554,0.0004017058,0.0000222716,0.00158622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01441664,"threshold_uncertainty_score":0.02866542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166786484843045,"score_gpt":0.1943099452895219,"score_spread":0.1826420804410915,"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."}}