{"id":"W4310595455","doi":"10.1021/acs.est.2c05255","title":"Material Stock and Embodied Greenhouse Gas Emissions of Global and Urban Road Pavement","year":2022,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Norges Forskningsråd; Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Stock (firearms); Per capita; Greenhouse gas; Agricultural economics; Environmental science; Population; Natural resource economics; Geography; Business; Environmental engineering; Economics; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002784459,0.0003763999,0.0001539787,0.001125751,0.0001070046,0.0008083169,0.0002999462,0.0002583601,0.0018771],"category_scores_gemma":[0.0007559031,0.0001622148,0.0003616819,0.001473624,0.0002417423,0.00123405,0.0003803261,0.0001813915,0.0004177199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008773382,"about_ca_system_score_gemma":0.000265335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01553001,"about_ca_topic_score_gemma":0.0221592,"domain_scores_codex":[0.9998783,0.00001939782,0.000007186829,0.00003039056,0.00004070537,0.00002396039],"domain_scores_gemma":[0.999616,0.0001000268,0.0001036476,0.00004492304,0.0001169679,0.0000183186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001657832,0.00006890627,0.7162899,0.000155887,0.0004294995,0.0003951976,0.0002381779,0.2346123,0.007982397,0.007526394,0.0008659551,0.03126962],"study_design_scores_gemma":[0.000004301276,0.00009286297,0.8969331,0.00006128626,0.0001663971,0.0001853481,0.000707514,0.08048483,0.01041918,0.003186368,0.007710059,0.00004871677],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898587,0.0002610416,0.00268863,0.00005195554,0.000007631251,0.00000775122,0.003312488,0.00002369099,0.003787989],"genre_scores_gemma":[0.9964834,0.0001558706,0.0007436427,0.000006277496,0.000003904233,0.000005520541,0.001741106,0.00001252778,0.0008476487],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01553001,"threshold_uncertainty_score":0.03087926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004734432232015029,"score_gpt":0.2199257629637424,"score_spread":0.2151913307317274,"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."}}