{"id":"W4409257704","doi":"10.3390/pr13041120","title":"Optimizing Solar PV Deployment in Manufacturing: A Morphological Matrix and Fuzzy TOPSIS Approach","year":2025,"lang":"en","type":"article","venue":"Processes","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Software deployment; Fuzzy logic; TOPSIS; Photovoltaic system; Matrix (chemical analysis); Computer science; Mathematical optimization; Process engineering; Mathematics; Materials science; Engineering; Operations research; Artificial intelligence; Electrical engineering; Composite material","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00282149,0.001197301,0.0008828625,0.003218948,0.000938196,0.002809848,0.001070873,0.0007740994,0.002584938],"category_scores_gemma":[0.004099102,0.0006897539,0.001741085,0.002692197,0.000744766,0.001385174,0.001267861,0.0007946922,0.0002367652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001761369,"about_ca_system_score_gemma":0.002261726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006095418,"about_ca_topic_score_gemma":0.009558031,"domain_scores_codex":[0.9979975,0.0009661881,0.0001428578,0.0001745264,0.0006025007,0.0001164787],"domain_scores_gemma":[0.9984905,0.0008660539,0.0002293589,0.00004865464,0.0003189728,0.00004644434],"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":[0.0001822445,0.000197929,0.004346373,0.0007931248,0.0003237742,0.0004924736,0.0007424551,0.780107,0.01386303,0.0259165,0.0008049165,0.1722301],"study_design_scores_gemma":[0.00002105887,0.0002425955,0.001334689,0.00008281028,0.00008296529,0.00008776187,0.0005941101,0.9791985,0.003118953,0.01363971,0.001553113,0.00004368808],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05761525,0.0003508242,0.9341242,0.0002955876,0.00003499105,0.0004168633,0.0001429901,0.0001300965,0.006889178],"genre_scores_gemma":[0.5206533,0.0006478478,0.4769945,0.00003723241,0.00001402525,0.0003171347,0.0001197214,0.00001823246,0.001197995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006095418,"threshold_uncertainty_score":0.01492167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1164318037414803,"score_gpt":0.4079726774332473,"score_spread":0.291540873691767,"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."}}