{"id":"W4391096344","doi":"10.1088/2634-4505/ad2153","title":"The carbon footprint of future engineered wood construction in Montreal","year":2024,"lang":"en","type":"article","venue":"Environmental Research Infrastructure and Sustainability","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Carbon footprint; Footprint; Environmental science; Waste management; Engineering; Greenhouse gas; Geology; Geography; Archaeology; Oceanography","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":[],"consensus_categories":[],"category_scores_codex":[0.001836513,0.0002479203,0.0002343217,0.0001083448,0.000261667,0.00008548498,0.0002963272,0.0001867298,0.0002269974],"category_scores_gemma":[0.0002254301,0.0001760526,0.00008633219,0.0004431045,0.002602496,0.0001511282,0.0006307016,0.0008893505,0.000004355209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002209449,"about_ca_system_score_gemma":0.00006036675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009740664,"about_ca_topic_score_gemma":0.0003990327,"domain_scores_codex":[0.9970425,0.0004131087,0.0004323933,0.0005962464,0.0007674015,0.0007483982],"domain_scores_gemma":[0.9988694,0.0003482101,0.00003914256,0.0005244931,0.000008906037,0.0002098035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002131278,0.0001439061,0.5986136,0.0002055992,0.0000298831,0.00005843766,0.003077453,0.001227372,0.00230738,0.001357748,0.00007055448,0.3926949],"study_design_scores_gemma":[0.0002714053,0.0001873928,0.9251835,0.00001061599,0.000007645078,0.00002258206,0.01312327,0.001983033,0.001195279,0.0517454,0.006095506,0.0001744093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948093,0.001238748,0.00002061911,0.000768814,0.0001341615,0.0008174824,0.00001432592,0.00002319589,0.002173387],"genre_scores_gemma":[0.9987919,0.0006215372,0.0001106032,0.000006690593,0.00006797443,0.00006167034,0.000006075557,0.00001926134,0.000314299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3925205,"threshold_uncertainty_score":0.9589004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00467253474728966,"score_gpt":0.2626111501917411,"score_spread":0.2579386154444515,"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."}}