{"id":"W2411461420","doi":"10.1016/j.apenergy.2016.05.130","title":"The calibration and validation of a model for predicting the performance of gas-fired tankless water heaters in domestic hot water applications","year":2016,"lang":"en","type":"article","venue":"Applied Energy","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Calibration; Inlet; Environmental science; Mean squared error; Range (aeronautics); Gas consumption; Water consumption; Energy consumption; Current (fluid); Process engineering; Statistics; Environmental engineering; Mathematics; Engineering; Thermodynamics; Mechanical engineering; Physics","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":[0.001123767,0.000883021,0.000603571,0.0004021512,0.0006335338,0.0006963846,0.0008898333,0.001254554,0.0009039199],"category_scores_gemma":[0.002152513,0.0004443759,0.0007069046,0.0004250681,0.0003877424,0.0007587019,0.0004122128,0.0008973086,0.0003378459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007483795,"about_ca_system_score_gemma":0.0008746202,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01356792,"about_ca_topic_score_gemma":0.007327089,"domain_scores_codex":[0.9996781,0.00008119639,0.00002459977,0.00008101694,0.00009661585,0.00003846875],"domain_scores_gemma":[0.998984,0.0005542799,0.00005934168,0.0001444397,0.0002374435,0.00002048409],"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":[0.0001127104,0.0001885341,0.004896478,0.00004389511,0.00003446175,0.00003163872,0.00003903956,0.9659566,0.01175196,0.0002239074,0.0003164834,0.01640412],"study_design_scores_gemma":[0.000009853394,0.00007213109,0.001447458,0.000002192632,0.000008721509,0.000006567538,0.000008287283,0.9911834,0.007025,0.00008732283,0.0001434821,0.000005553688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8966729,0.0001629904,0.09940277,0.0001297163,0.0000615618,0.0000839612,0.0003696228,0.0008025616,0.002313913],"genre_scores_gemma":[0.9930394,0.0000387021,0.006153511,0.00001095748,0.000003630766,0.00003335795,0.0001909091,0.00002287829,0.0005065382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01356792,"threshold_uncertainty_score":0.0269779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007107313721832339,"score_gpt":0.1849386606390433,"score_spread":0.1778313469172109,"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."}}