{"id":"W4404240770","doi":"10.1093/ijlct/ctae214","title":"Enhancing thermal efficiency of passive solar heating systems through copper chip integration: experimental investigation and analysis","year":2024,"lang":"en","type":"article","venue":"International Journal of Low-Carbon Technologies","topic":"Solar Thermal and Photovoltaic Systems","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Copper; Thermal; Chip; Materials science; Thermal analysis; Passive solar building design; Engineering physics; Environmental science; Metallurgy; Engineering; Electrical engineering; Meteorology; 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":[0.0003464241,0.0001723182,0.0003567397,0.0005229015,0.00004533098,0.0001370085,0.0003641647,0.0001541069,0.00001406214],"category_scores_gemma":[0.0002315283,0.0001284302,0.0001765136,0.0004666803,0.0001713977,0.0003224403,0.00008896909,0.0002783428,0.000001646418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00013559,"about_ca_system_score_gemma":0.00005989422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007855867,"about_ca_topic_score_gemma":0.00002475533,"domain_scores_codex":[0.9982761,0.00008220474,0.000774373,0.000190853,0.0005365221,0.0001399134],"domain_scores_gemma":[0.9988062,0.0001930532,0.0005425774,0.0001347552,0.0002970149,0.00002633222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005667001,0.00004990433,0.005077847,0.0000653747,0.001367098,0.00006713243,0.004088331,0.003122793,0.9740591,0.006512209,0.0000107084,0.00552284],"study_design_scores_gemma":[0.0002671588,0.0001643115,0.0006101115,0.0008986374,0.0001308093,0.0001142386,0.01085579,0.02225454,0.9635862,0.000883679,0.0000825902,0.0001519667],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879362,0.007587511,0.001998321,0.0002252704,0.001220061,0.00009480153,0.000007710333,0.0001398487,0.0007902706],"genre_scores_gemma":[0.9992128,0.00009685597,0.0004089789,0.00001577211,0.0001998531,0.00001290956,0.000006297897,0.0000155314,0.00003101093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01913175,"threshold_uncertainty_score":0.523723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486186574270167,"score_gpt":0.2617070504210411,"score_spread":0.2468451846783395,"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."}}