{"id":"W2315836416","doi":"10.5383/ijtee.02.01.004","title":"Indoor Energy Analysis of Food Distribution Warehouse","year":2010,"lang":"en","type":"article","venue":"International Journal of Thermal and Environmental Engineering","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Prince Mohammad Bin Fahd University","keywords":"Warehouse; Distribution (mathematics); Environmental science; Computer science; Business; Mathematics; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001148441,0.0002191928,0.0003156929,0.000381261,0.0003388143,0.000685889,0.000272241,0.0003206426,0.003308974],"category_scores_gemma":[0.0001629948,0.000188047,0.0005671448,0.0004163716,0.0001198755,0.0002919362,0.0001949664,0.0001342301,0.0004570594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005163961,"about_ca_system_score_gemma":0.0002781405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003853745,"about_ca_topic_score_gemma":0.004035407,"domain_scores_codex":[0.999915,0.00001035993,0.00000308589,0.00001415616,0.00003545721,0.00002196513],"domain_scores_gemma":[0.9999462,0.00002037332,0.000004634258,0.000006099256,0.00001860467,0.000003994417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002127889,0.0001251059,0.02165712,0.0000817631,0.00004675688,0.000764067,0.0001186811,0.9130613,0.04346592,0.002460227,0.000633891,0.0173724],"study_design_scores_gemma":[0.00001486781,0.0001067718,0.02426754,0.000008358337,0.00002106645,0.0001413968,0.0002870052,0.9572813,0.01514373,0.0007843538,0.00192478,0.00001883169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627939,0.0001243148,0.02516459,0.00004440255,0.00001309825,0.0000190835,0.0003680625,0.00009517057,0.01137748],"genre_scores_gemma":[0.996376,0.00005201083,0.001182079,0.00000502271,0.000001524991,0.000007909884,0.0002242335,0.00001951303,0.002131672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003853745,"threshold_uncertainty_score":0.01106966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002719494420339523,"score_gpt":0.1633716203687968,"score_spread":0.1606521259484573,"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."}}