{"id":"W4386432658","doi":"10.1007/978-981-19-9822-5_225","title":"Simulation Study of ERV Pre-heating for Arctic Residential Applications","year":2023,"lang":"en","type":"book-chapter","venue":"Environmental science and engineering","topic":"Solar Thermal and Photovoltaic Systems","field":"Energy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Building-integrated photovoltaics; Environmental science; Electricity; Arctic; Photovoltaic system; Windshield; Atmospheric sciences; Meteorology; Environmental engineering; Engineering; Electrical engineering; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002301843,0.0001235826,0.0001438853,0.00009715866,0.000130273,0.00002068639,0.0001225942,0.00005780543,0.00002506054],"category_scores_gemma":[0.00002476821,0.0001249548,0.00003125308,0.0000455047,0.00006160597,0.00008617232,0.00007373533,0.00007009522,0.00001055284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008196585,"about_ca_system_score_gemma":0.000007687165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002413818,"about_ca_topic_score_gemma":0.00002410114,"domain_scores_codex":[0.999091,0.000002574507,0.0002108483,0.0002537734,0.0003044725,0.0001373128],"domain_scores_gemma":[0.999576,0.0001105148,0.00009739846,0.0001577679,0.000008147178,0.00005017233],"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":[0.00001712339,0.00005475605,0.0005611605,0.0002135792,0.00006621062,0.000001520641,0.001759771,0.9219838,0.06204142,0.003496862,0.000002840848,0.009800931],"study_design_scores_gemma":[0.002565295,0.001366552,0.05879011,0.0008974269,0.000472616,0.00001417341,0.00246874,0.8725215,0.005249195,0.004897907,0.0486109,0.002145613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9746678,0.0004438308,0.006676218,0.000008665923,0.0008392719,0.004391824,0.00008983275,0.0002544061,0.01262813],"genre_scores_gemma":[0.9890211,0.000009005115,0.00007595142,0.000002311074,0.0001386969,0.0001000716,0.00001098509,0.00003038271,0.01061147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05822895,"threshold_uncertainty_score":0.509551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597550206031006,"score_gpt":0.2246779503013075,"score_spread":0.2087024482409975,"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."}}