{"id":"W4385420352","doi":"10.18280/ijsdp.180701","title":"Panergy Analysis: Tool for Decision-Making in Economy, Energy, Environment and Engineering","year":2023,"lang":"en","type":"article","venue":"International Journal of Sustainable Development and Planning","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Energy economics; Engineering economics; Engineering; Environmental economics; Business; Economics; Microeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002786386,0.0001186416,0.0003231816,0.002588701,0.00009430746,0.0004586132,0.0003354899,0.00004584198,0.0000382148],"category_scores_gemma":[0.001361612,0.00009715658,0.00008266124,0.0005566249,0.00001280892,0.0004116551,0.00019275,0.00007749475,0.000001725548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009928583,"about_ca_system_score_gemma":0.00008151958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007997658,"about_ca_topic_score_gemma":0.000005094891,"domain_scores_codex":[0.997862,0.00002658379,0.001007401,0.0002336103,0.0006375384,0.0002328968],"domain_scores_gemma":[0.9963328,0.002796973,0.0003826773,0.00008340969,0.0003409991,0.00006311463],"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":[0.0004511588,0.00003210628,0.2314054,0.00002425086,0.0008332542,0.003167272,0.007458697,0.4143364,0.00002432994,0.02625747,0.002239408,0.3137703],"study_design_scores_gemma":[0.001165814,0.00005847511,0.5103774,0.0004249577,0.00004411473,0.0001534089,0.02549146,0.1666035,0.00002422592,0.06494591,0.2302929,0.0004178243],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8052232,0.0007895246,0.1934585,0.00008925372,0.0002296324,0.000059952,0.000001886002,0.000007093477,0.000140981],"genre_scores_gemma":[0.9898319,0.00001851113,0.009673484,0.00004745018,0.0001069877,0.000005963813,0.000001926374,0.000005191206,0.0003085495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3133525,"threshold_uncertainty_score":0.4422417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03775317092192163,"score_gpt":0.3225803689812238,"score_spread":0.2848271980593021,"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."}}