{"id":"W7143294503","doi":"10.60087/jaigs.v6i1.461","title":"Thermal Energy Districts as a Core Component of Positive Energy Districts","year":2024,"lang":"","type":"article","venue":"Journal of Artificial Intelligence General science (JAIGS) ISSN 3006-4023","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Renewable energy; Energy transition; Greenhouse gas; Efficient energy use; Energy engineering; Energy policy; Energy consumption; Energy conservation; Environmental impact of the energy industry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001221923,0.0003403899,0.0002542652,0.0008081033,0.001694654,0.004653654,0.001081426,0.0008179219,0.007212372],"category_scores_gemma":[0.001572568,0.0002366416,0.0003032702,0.001481328,0.003163659,0.003045409,0.003512777,0.001044871,0.0009235607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00272535,"about_ca_system_score_gemma":0.004134416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003955988,"about_ca_topic_score_gemma":0.01634449,"domain_scores_codex":[0.9984434,0.0006045022,0.00004354984,0.0001832821,0.0003769023,0.00034825],"domain_scores_gemma":[0.9990571,0.0002098668,0.0001216429,0.0001600604,0.0002904721,0.0001609235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006153506,0.00009032292,0.007075138,0.0007319706,0.00002378958,0.0004234931,0.002494168,0.008380024,0.003232958,0.8419257,0.006584271,0.1289766],"study_design_scores_gemma":[0.00002204991,0.0001902652,0.02144255,0.0007893872,0.00008405095,0.0008104072,0.01306148,0.006797974,0.008955504,0.2292584,0.7185085,0.00007944347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1698457,0.004592898,0.1693671,0.008128193,0.0004252371,0.0006660231,0.0004283618,0.0005835883,0.645963],"genre_scores_gemma":[0.9534461,0.00146357,0.02347483,0.0003815354,0.0000504993,0.0001315827,0.000160045,0.0000678683,0.02082408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007212372,"threshold_uncertainty_score":0.02412778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02499719511317461,"score_gpt":0.2755972251336503,"score_spread":0.2506000300204757,"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."}}