{"id":"W4253074163","doi":"10.32920/ryerson.14665434.v1","title":"Heat Pump Water Heater For Cold Climate – Canada","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Building Energy and Comfort Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"TRNSYS; Environmental science; Storage water heater; Coefficient of performance; Storage heater; Energy consumption; Electricity; Heat pump; Environmental engineering; Nuclear engineering; Meteorology; Water heater; Inlet; Engineering; Mechanical engineering; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0001341672,0.0002483269,0.0002740674,0.0002023977,0.0007474194,0.0004699798,0.0004234079,0.000228097,0.005283413],"category_scores_gemma":[0.0001519406,0.0001341017,0.0004312974,0.0003952433,0.0001931811,0.0003955741,0.0003297988,0.0002921979,0.0008129792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002075357,"about_ca_system_score_gemma":0.002290275,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2285378,"about_ca_topic_score_gemma":0.3174241,"domain_scores_codex":[0.9998633,0.000008608527,0.000003165891,0.00001975573,0.00008086103,0.00002426027],"domain_scores_gemma":[0.9999396,0.00000615988,0.000004086588,0.000006611108,0.00003746348,0.000006214389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001110523,0.0003572229,0.01567069,0.001078387,0.00008045411,0.0006037345,0.0005254349,0.3254733,0.4098756,0.0159831,0.02049359,0.2087481],"study_design_scores_gemma":[0.0001298041,0.0004661663,0.03521208,0.00005544978,0.00009109792,0.000201458,0.0004184562,0.7063955,0.1621552,0.001643868,0.09312125,0.0001097759],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.773591,0.001740174,0.134124,0.0003347961,0.000213502,0.0003215173,0.002054125,0.002226553,0.08539426],"genre_scores_gemma":[0.9589562,0.0003776339,0.008956732,0.00001780288,0.000007290466,0.00005217236,0.0007082179,0.00005951171,0.03086431],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7714622,"threshold_uncertainty_score":0.4544151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006818046364375122,"score_gpt":0.1772493732829904,"score_spread":0.1704313269186153,"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."}}