{"id":"W4296201467","doi":"10.1016/j.renene.2022.09.051","title":"A granular multicriteria group decision making for renewable energy planning problems","year":2022,"lang":"en","type":"article","venue":"Renewable Energy","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Canada First Research Excellence Fund; University of Alberta","keywords":"Pairwise comparison; Ranking (information retrieval); Computer science; Analytic hierarchy process; Group decision-making; Interpretability; Multiple-criteria decision analysis; Data mining; Relevance (law); Operations research; Management science; Machine learning; Artificial intelligence; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006058465,0.0007162673,0.001191124,0.001705632,0.002229822,0.001253448,0.003117716,0.0002524992,0.002677836],"category_scores_gemma":[0.003062568,0.000660717,0.0006261618,0.002613129,0.0001175952,0.0008593254,0.002089701,0.0002512879,0.00002049663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004438996,"about_ca_system_score_gemma":0.0002131745,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008237995,"about_ca_topic_score_gemma":0.002328993,"domain_scores_codex":[0.9888939,0.0009179651,0.002404433,0.002350485,0.003917216,0.001516051],"domain_scores_gemma":[0.9903638,0.005409213,0.001033675,0.002254356,0.000556619,0.0003822852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006020143,0.0002079698,0.0005122679,0.00001459276,0.0000303772,0.00009109935,0.0004142824,0.868656,0.02372528,0.001055883,0.05890558,0.04578465],"study_design_scores_gemma":[0.001607328,0.0002614697,0.00009126139,0.0001413209,0.00002725762,0.00009352747,0.0006541372,0.3167825,0.001696439,0.09105723,0.5869464,0.0006410812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01210233,0.002539432,0.9771515,0.0001350248,0.003690345,0.0004355104,0.000170664,0.0003102008,0.003464957],"genre_scores_gemma":[0.9064339,0.00003755456,0.07841817,0.00138193,0.0006096432,0.001081757,0.0001277553,0.0002026548,0.01170659],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8987334,"threshold_uncertainty_score":0.9997833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09472860775902023,"score_gpt":0.3692294919305911,"score_spread":0.2745008841715708,"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."}}