{"id":"W1907834434","doi":"10.3963/jmpm.v3i1.122","title":"Aircraft Eco-assembly: a strategy to reduce the ecological footprint of aerospace industry","year":2015,"lang":"en","type":"article","venue":"Journal of Modern Project Management","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université du Québec à Montréal","funders":"","keywords":"Aerospace; Ecological footprint; Environmental impact assessment; Carbon footprint; Footprint; Environmental pollution; Engineering; Sustainable development; Environmental science; Greenhouse gas; Environmental protection; Aerospace engineering","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":[0.001494926,0.000169921,0.0002517975,0.00006555556,0.00006507304,0.00004141039,0.0005818639,0.0001088453,0.0001028383],"category_scores_gemma":[0.00007272009,0.0001064747,0.0001209236,0.0002412042,0.0001470388,0.0001681772,0.0006587378,0.0004106748,0.00002278815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007872639,"about_ca_system_score_gemma":0.00005085125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001136136,"about_ca_topic_score_gemma":0.00004647004,"domain_scores_codex":[0.9980951,0.0001644131,0.0004846979,0.0002125933,0.000712977,0.0003302473],"domain_scores_gemma":[0.9990697,0.00003072635,0.0003023266,0.0003597178,0.00002382446,0.0002137027],"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":[0.00190209,0.005977654,0.2612969,0.0002089805,0.0006352225,0.0006383102,0.01359439,0.3670306,0.01099068,0.0009972263,0.07481696,0.261911],"study_design_scores_gemma":[0.003115911,0.006453872,0.9173344,0.00008983225,0.0002605043,0.0001721181,0.02210448,0.002406329,0.008548371,0.01109271,0.02769263,0.0007287767],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841757,0.00004526539,0.001349817,0.001557906,0.00009503693,0.0006539796,0.000001303376,0.000008890249,0.01211205],"genre_scores_gemma":[0.9960158,0.0000209337,0.002027027,0.0002453532,0.00003917045,0.00001691272,2.730728e-7,0.00001164645,0.001622837],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6560376,"threshold_uncertainty_score":0.4341911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04242930184902193,"score_gpt":0.3082939068029,"score_spread":0.265864604953878,"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."}}