{"id":"W2124665406","doi":"10.1115/1.4001674","title":"Geometric Optimization of Concentrating Solar Collectors using Monte Carlo Simulation","year":2010,"lang":"en","type":"article","venue":"Journal of Solar Energy Engineering","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Monte Carlo method; Computer science; Mathematical optimization; Process (computing); Linear programming; Optimal design; Quasi-Monte Carlo method; Algorithm; Mathematics; Hybrid Monte Carlo; Markov chain Monte Carlo; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001233091,0.0006834004,0.0008476704,0.0005688824,0.0004890751,0.0007238315,0.0007056513,0.0008380198,0.001556269],"category_scores_gemma":[0.002709559,0.0006148196,0.0006434206,0.0006536495,0.0007512448,0.0005366274,0.0005690471,0.000472648,0.0002556494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083397,"about_ca_system_score_gemma":0.000960013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002466271,"about_ca_topic_score_gemma":0.002456226,"domain_scores_codex":[0.9994519,0.0001967036,0.00001769556,0.00005939439,0.0002278988,0.00004633428],"domain_scores_gemma":[0.9988424,0.0008218545,0.0001155103,0.00006315632,0.000135748,0.00002137781],"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":[0.00000705179,0.000003810255,0.00007569858,0.00000999539,0.000004491003,0.000006516461,0.000005383559,0.9946787,0.0004634041,0.002125892,0.00004309121,0.002575845],"study_design_scores_gemma":[0.000004037178,0.000008113757,0.00004106298,0.000001955494,0.000001977828,0.000004829957,0.000001514726,0.9985583,0.0004309961,0.0007557584,0.0001889657,0.000002399054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01488073,0.0001309625,0.9803845,0.00006801384,0.00001148371,0.00005235722,0.00001589612,0.0002412618,0.004214805],"genre_scores_gemma":[0.6076977,0.0003341349,0.3890042,0.00006731079,0.00002750437,0.0003555399,0.00008004842,0.000145318,0.002288233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002466271,"threshold_uncertainty_score":0.007860661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00986101067755974,"score_gpt":0.216238864171887,"score_spread":0.2063778534943273,"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."}}