{"id":"W4401333231","doi":"10.3389/fenrg.2024.1447655","title":"An experimental analysis and deep learning model to assess the cooling performance of green walls in humid climates","year":2024,"lang":"en","type":"article","venue":"Frontiers in Energy Research","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"","keywords":"Urban heat island; Environmental science; Climate change; Urbanization; Meteorology; Urban climate; Deep learning; Atmospheric sciences; Computer science; Machine learning; Geography; Ecology; Geology","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":[0.001085034,0.00007124548,0.0001322101,0.0003792479,0.00009297395,0.00004923595,0.0002170512,0.00004670576,0.00004364234],"category_scores_gemma":[0.00002225423,0.0000563276,0.00002246688,0.001242389,0.0001579794,0.000259781,0.0001604707,0.0002209251,0.000002821414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002183328,"about_ca_system_score_gemma":0.0000125147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00249554,"about_ca_topic_score_gemma":0.001481702,"domain_scores_codex":[0.9986892,0.0001968011,0.0001662812,0.0002782673,0.000379699,0.0002897178],"domain_scores_gemma":[0.9996833,0.00008214905,0.00001226037,0.0001530296,0.000008722259,0.00006060018],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003738695,0.00002757303,0.6236298,0.00001026072,0.00001478608,0.000003524612,0.003308058,0.3454361,0.0177121,0.00003943783,0.00006828421,0.009712701],"study_design_scores_gemma":[0.00006923163,0.00008093804,0.04793749,0.00001967749,0.000006538957,4.834329e-7,0.001397033,0.9335977,0.01664046,0.00009237482,0.00009346064,0.00006463462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943609,0.0006806114,0.004255,0.0000459133,0.00002957794,0.00007814698,0.000001341175,0.0000101021,0.0005383578],"genre_scores_gemma":[0.9965283,0.0002376851,0.002851272,0.00001439177,0.00001247345,0.00004585334,0.000007919245,0.00001033847,0.0002917178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5881616,"threshold_uncertainty_score":0.3772527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03989242282247278,"score_gpt":0.3307290204271121,"score_spread":0.2908365976046393,"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."}}