{"id":"W1532658188","doi":"10.12962/j23373539.v2i3.5181","title":"Analisis Pengurangan Emisi CO2 Melalui Manajemen Penggunaan Listrik dan Ketersediaan Ruang Terbuka Hijau di Gedung Perkantoran Pemerintah Kota Surabaya","year":2013,"lang":"id","type":"article","venue":"Jurnal Teknik ITS","topic":"Waste Management and Recycling","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Engineering","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":[0.0006555005,0.0007534649,0.0007950137,0.001615148,0.001650001,0.001997868,0.0006036898,0.0009401754,0.008872743],"category_scores_gemma":[0.0008565077,0.0004600328,0.0009741641,0.001585174,0.0005242844,0.001091213,0.0008592907,0.001321457,0.002202061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009516861,"about_ca_system_score_gemma":0.001229868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02395824,"about_ca_topic_score_gemma":0.05140007,"domain_scores_codex":[0.9990141,0.00005796817,0.00005140605,0.0002766541,0.0004592445,0.0001405617],"domain_scores_gemma":[0.9992399,0.0001539356,0.00009106845,0.00004930093,0.0004189544,0.00004679788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001760113,0.0003703574,0.1735267,0.00345365,0.0004845328,0.001273612,0.003145332,0.001654653,0.7075568,0.002011742,0.007260607,0.09750204],"study_design_scores_gemma":[0.00003311365,0.0008557856,0.331989,0.0004050661,0.0004833013,0.0008833917,0.00870872,0.004844584,0.5414982,0.001621331,0.1084872,0.000190125],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9136522,0.00718888,0.01617794,0.00079923,0.0005141864,0.0005980147,0.01535687,0.0006934183,0.04501929],"genre_scores_gemma":[0.9178529,0.005335982,0.01570308,0.0008351626,0.00009591477,0.000631341,0.007298897,0.0004347655,0.05181196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02395824,"threshold_uncertainty_score":0.04763758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469550379117244,"score_gpt":0.2262139435967509,"score_spread":0.2115184398055785,"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."}}