{"id":"W2769008159","doi":"10.5539/ass.v13n12p125","title":"Drivers of Residential Energy Saving","year":2017,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Energy Efficiency and Management","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Environmental economics; Efficient energy use; Business; Energy current; Energy consumption; Economics; Engineering; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003478104,0.0001123953,0.0001765129,0.00073966,0.0002982825,0.0008457897,0.0002516698,0.0002591392,0.008184325],"category_scores_gemma":[0.001314926,0.0001473819,0.0003774664,0.001698775,0.0002696717,0.0004880141,0.0006850913,0.0005459688,0.0005137299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006605196,"about_ca_system_score_gemma":0.0007121079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01299182,"about_ca_topic_score_gemma":0.02053593,"domain_scores_codex":[0.9996973,0.00005577243,0.00002744669,0.00003437819,0.0001075131,0.00007765169],"domain_scores_gemma":[0.9989557,0.0002468768,0.000391799,0.00005076461,0.0001835385,0.0001712925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002225095,0.00008201384,0.9864281,0.00005527963,0.0000464471,0.0002062658,0.0008945076,0.0004934567,0.000345252,0.002554338,0.0008334928,0.008038707],"study_design_scores_gemma":[0.000001073356,0.00001523107,0.992776,0.00002127628,0.00001557253,0.0001453802,0.003008631,0.0006938434,0.0001094695,0.0002900156,0.002915908,0.000007552024],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912599,0.0001815696,0.0002202234,0.0006057955,0.000006797541,0.00002082578,0.0006987272,0.00001319504,0.006992905],"genre_scores_gemma":[0.9981363,0.0001693356,0.000095483,0.00001997354,0.000004191407,0.000006153183,0.0002717628,0.000003199196,0.001293579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01299182,"threshold_uncertainty_score":0.02737927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158460055845078,"score_gpt":0.2667847610168103,"score_spread":0.2552001604583595,"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."}}