{"id":"W1981948396","doi":"10.1016/j.solener.2013.12.001","title":"Optimization of a residential solar combisystem for minimum life cycle cost, energy use and exergy destroyed","year":2013,"lang":"en","type":"article","venue":"Solar Energy","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Concordia University","keywords":"Exergy; Payback period; Electricity; Exergy efficiency; Environmental science; Solar energy; Process engineering; Computer science; Engineering; Electrical engineering; Economics; Production (economics); Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007739045,0.0001983038,0.0002726984,0.0001390075,0.0001011556,0.0001055244,0.0001338154,0.0001912132,0.00003693769],"category_scores_gemma":[0.00004700929,0.0002118149,0.00007498266,0.0001627068,0.00003946444,0.0005031301,0.00004289826,0.00005388154,3.805982e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003178703,"about_ca_system_score_gemma":0.00002950309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000843605,"about_ca_topic_score_gemma":0.0001241915,"domain_scores_codex":[0.9989492,0.00004608863,0.0003690376,0.0002193378,0.0001406998,0.0002756584],"domain_scores_gemma":[0.9992842,0.00009076633,0.00009579792,0.0002552533,0.0001429093,0.0001310536],"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":[0.00002534835,0.0000242378,0.00007433025,0.00005023878,0.0000744924,5.958542e-7,0.00003406913,0.989477,0.001542318,0.005668425,0.001440539,0.001588429],"study_design_scores_gemma":[0.0007034168,0.00005951344,0.00009005661,0.00004661482,0.00003721898,0.000004346168,0.00002981035,0.9860227,0.01004199,0.000372009,0.002361395,0.0002308834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05235244,0.0004338425,0.9463051,0.00003190616,0.0003535374,0.0001429102,0.00001499847,0.0002029514,0.0001623394],"genre_scores_gemma":[0.9832304,0.0003536512,0.01558321,0.00008144593,0.0001073729,0.0002066999,0.0001272642,0.0000739832,0.000235967],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.930878,"threshold_uncertainty_score":0.8637561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009445275886975999,"score_gpt":0.1862280823533034,"score_spread":0.1767828064663274,"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."}}