{"id":"W2020938520","doi":"10.1016/j.buildenv.2015.03.022","title":"Methodological challenges and developments in LCA of low energy buildings: Application to biogenic carbon and global warming assessment","year":2015,"lang":"en","type":"article","venue":"Building and Environment","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":182,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Life-cycle assessment; Global warming; Environmental science; Greenhouse gas; Climate change; Environmental impact assessment; Civil engineering; Engineering; 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":[0.0008942613,0.0001860527,0.00025309,0.00003731135,0.00004610643,0.00001185725,0.00009304216,0.00009173745,0.000007353165],"category_scores_gemma":[0.00003928518,0.0001693457,0.00001760534,0.00007436437,0.0002156369,0.00008663037,0.0005623416,0.00006655081,9.779658e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000587905,"about_ca_system_score_gemma":0.000007140811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005585189,"about_ca_topic_score_gemma":0.00004052557,"domain_scores_codex":[0.9985549,0.0001282514,0.0002608594,0.0005077117,0.0002647833,0.0002834578],"domain_scores_gemma":[0.9994308,0.00005326097,0.00007178324,0.0001664497,0.000001523324,0.0002761183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005240425,0.0001896005,0.6606759,0.00003907872,0.00001478939,0.000005279242,0.001127532,0.0011908,0.01693309,0.0007018177,0.000005076025,0.3190646],"study_design_scores_gemma":[0.0005347338,0.0002090266,0.989639,0.00002394375,0.00001370118,0.00001486256,0.0008922305,0.000910403,0.002502723,0.003072942,0.00193517,0.00025121],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948987,0.001174662,0.002535824,0.0003208168,0.00001771357,0.0002167274,0.000002240958,0.0000107399,0.0008225456],"genre_scores_gemma":[0.9679092,0.001776212,0.0301628,0.00007392225,0.000008275418,0.00004582949,0.000001572579,0.000008269111,0.00001388374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3289631,"threshold_uncertainty_score":0.6905716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05222778061043197,"score_gpt":0.3129443662454474,"score_spread":0.2607165856350154,"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."}}