{"id":"W2994757686","doi":"","title":"Energy and Carbon Exchanges Along an Urbanization Gradient in Montreal, Canada","year":2010,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Urbanization; Energy (signal processing); Meteorology; Geography; Environmental science; Economic growth; Economics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001783684,0.0002486138,0.000291772,0.0010571,0.003294734,0.001798541,0.000658377,0.0004096899,0.005615806],"category_scores_gemma":[0.0005702396,0.0002316902,0.0004158705,0.002958783,0.0006481932,0.0005910731,0.0007574726,0.0004597078,0.0002798706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03883829,"about_ca_system_score_gemma":0.02261441,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982102,"about_ca_topic_score_gemma":0.9994776,"domain_scores_codex":[0.9997793,0.00002063302,0.000007082214,0.00004061235,0.00005933389,0.0000930371],"domain_scores_gemma":[0.9996309,0.00002665297,0.00004123713,0.00000761022,0.0002098943,0.00008369434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00047025,0.0001660609,0.934607,0.0001396576,0.0002566092,0.0007752615,0.004879999,0.007432825,0.004330636,0.003740444,0.01605919,0.02714206],"study_design_scores_gemma":[0.00001064263,0.000008273801,0.9931163,0.00001574211,0.00001874149,0.00002341336,0.001593085,0.001165807,0.0001931342,0.00005625691,0.003781068,0.00001746012],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871936,0.0003787146,0.0001395292,0.0008215608,0.00001446905,0.00003393446,0.003740726,0.00002892054,0.007648491],"genre_scores_gemma":[0.9932601,0.0002207147,0.0002359763,0.00006243447,0.000005090151,0.00001157338,0.0007114554,0.00001085044,0.005481717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03883829,"threshold_uncertainty_score":0.2817929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005469666899328063,"score_gpt":0.1940068972394585,"score_spread":0.1885372303401305,"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."}}