{"id":"W3151297347","doi":"10.1111/jiec.13122","title":"A comprehensive set of global scenarios of housing, mobility, and material efficiency for material cycles and energy systems modeling","year":2021,"lang":"en","type":"article","venue":"Journal of Industrial Ecology","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Industrial ecology; Scenario analysis; Environmental economics; Life-cycle assessment; Resource efficiency; Computer science; Efficient energy use; Energy modeling; Built environment; Environmental resource management; Sustainability; Environmental science; Business; Civil engineering; Economics; Engineering; Ecology; Production (economics)","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0003915424,0.000123426,0.0004966553,0.0000239297,0.00006244679,0.00002451381,0.0001050964,0.0002126611,0.0001037652],"category_scores_gemma":[0.0001383008,0.0001071888,0.00006895911,0.00007654711,0.000372386,0.000134208,0.0002322718,0.00008214748,1.093238e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002423928,"about_ca_system_score_gemma":0.0000927782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006087492,"about_ca_topic_score_gemma":0.0000788262,"domain_scores_codex":[0.9985824,0.0001879768,0.000677472,0.0001693019,0.0001713099,0.0002115916],"domain_scores_gemma":[0.9992291,0.00009012041,0.0004262264,0.000105508,0.00004675215,0.00010233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005741719,0.001294538,0.6671546,0.0004616299,0.000280533,0.0001175505,0.0009276034,0.1556675,0.1587375,0.0004011157,0.0004747161,0.008740969],"study_design_scores_gemma":[0.06467451,0.03369717,0.4155553,0.001195268,0.002238172,0.006178911,0.05687237,0.2167931,0.1761042,0.01735895,0.005733694,0.003598382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986486,0.00006537556,0.0002146375,0.00008025804,0.0006780002,0.0001485982,0.000131184,0.000002278538,0.00003106663],"genre_scores_gemma":[0.9994978,0.00003948547,0.0002663521,0.00001827024,0.000159837,0.000002642546,0.00000400817,0.000006194957,0.000005383599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2515993,"threshold_uncertainty_score":0.4371032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02816034406317473,"score_gpt":0.2666319355304014,"score_spread":0.2384715914672267,"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."}}