{"id":"W4381571074","doi":"10.3390/designs7030073","title":"Toward Positive Energy Districts by Urban–Industrial Energy Exchange","year":2023,"lang":"en","type":"article","venue":"Designs","topic":"Sustainable Industrial Ecology","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Industrial symbiosis; Carbon footprint; Environmental economics; Renewable energy; Efficient energy use; Sustainable development; Factory (object-oriented programming); Business; Ecological footprint; Greenhouse gas; Environmental planning; Computer science; Environmental science; Engineering; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001678176,0.0002630262,0.0003007362,0.0002549522,0.00008727821,0.0000510518,0.0002696057,0.0004567548,0.0003108323],"category_scores_gemma":[0.0001480919,0.0002941599,0.00008554759,0.00103149,0.0000481535,0.000131856,0.00007892962,0.0002149735,0.0001113974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004639666,"about_ca_system_score_gemma":0.00009619329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004760167,"about_ca_topic_score_gemma":0.00002435093,"domain_scores_codex":[0.9983574,0.0001146537,0.0002703235,0.0002983078,0.0002006663,0.0007586501],"domain_scores_gemma":[0.9991444,0.0003309315,0.00004231197,0.0002390962,0.00005160823,0.0001916008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004109286,0.00002771978,0.00005062703,0.00001214778,0.0001166332,0.0003511297,0.0002351024,0.004065237,0.001548624,0.002903023,0.9674819,0.02316679],"study_design_scores_gemma":[0.002220468,0.0003502501,0.0001431914,0.00002483849,0.00007139397,0.00002295439,0.0005016333,0.02204881,0.0273165,0.0007755469,0.9456685,0.000855919],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2750538,0.009651287,0.3576433,0.01033323,0.04636873,0.003927032,0.003864771,0.02964604,0.2635118],"genre_scores_gemma":[0.9901857,0.0001493179,0.0000208493,0.0001682483,0.00127508,0.0001718237,0.0003830917,0.0001000791,0.007545837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7151319,"threshold_uncertainty_score":0.9999511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05556671594819414,"score_gpt":0.2216112133248557,"score_spread":0.1660444973766616,"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."}}