{"id":"W2132129307","doi":"","title":"Making the Most of Energy Data: A Handbook for Facility Managers, Owners, and Operators","year":2012,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Pacific Northwest National Laboratory; Lawrence Berkeley National Laboratory; Building Technologies Program; U.S. Department of Energy","keywords":"Facility management; Energy (signal processing); Division (mathematics); Efficient energy use; Engineering; Architectural engineering; Operations research; Engineering management; Library science; Management; Aeronautics; Computer science; Business; Marketing; Economics; Mathematics; Electrical engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0003967786,0.0002721766,0.0002639196,0.00009688986,0.0002451829,0.0004704662,0.0008157311,0.0001055931,0.0001130882],"category_scores_gemma":[0.0002063441,0.0001861395,0.00008758195,0.000308056,0.0002014997,0.00359636,0.0009170125,0.0001513175,0.00004107738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001453599,"about_ca_system_score_gemma":0.00003393578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002772593,"about_ca_topic_score_gemma":0.000010538,"domain_scores_codex":[0.998262,0.00008911709,0.0004176756,0.0004291055,0.0002635431,0.0005385284],"domain_scores_gemma":[0.9985723,0.0002327985,0.0001363369,0.0008754653,0.00002448695,0.0001586269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006680348,0.00104208,0.09050798,0.000693915,0.0007180068,0.00001620782,0.0003361145,0.0009287366,0.0003455038,0.6411121,0.07574347,0.1878878],"study_design_scores_gemma":[0.0004027975,0.00004090287,0.0007711421,0.00005622309,0.00004672504,0.000003265763,0.0001271715,0.0004224792,0.001792529,0.002096296,0.9939595,0.0002809157],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4503636,0.04859067,0.07550196,0.005633775,0.002820329,0.003673882,0.04817542,0.002202101,0.3630382],"genre_scores_gemma":[0.9940291,0.00008282597,0.0008605291,0.0009734302,0.0001475492,0.00004955276,0.001340843,0.0000434402,0.00247273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9182161,"threshold_uncertainty_score":0.7590547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520945342968903,"score_gpt":0.2439551380096327,"score_spread":0.2087456845799437,"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."}}