{"id":"W2568193293","doi":"10.1016/j.tele.2017.01.001","title":"ICT and environmental sustainability: A global perspective","year":2017,"lang":"en","type":"article","venue":"Telematics and Informatics","topic":"Green IT and Sustainability","field":"Engineering","cited_by":627,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"European Commission","keywords":"Information and Communications Technology; Developing country; Sample (material); Sustainability; Business; Scale (ratio); Work (physics); Environmental economics; Industrial organization; Economics; Economic growth; Computer science; Engineering; Geography","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":[0.0001781306,0.0001386734,0.0001849361,0.00002105729,0.0002759239,0.0002111218,0.0001212011,0.00006401449,0.00001019901],"category_scores_gemma":[0.0001377023,0.0001244368,0.00002727394,0.00001885099,0.0002325277,0.0004124981,0.0001378907,0.0000970128,0.000002706864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002640603,"about_ca_system_score_gemma":0.00001858517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002905049,"about_ca_topic_score_gemma":0.00001202034,"domain_scores_codex":[0.9993467,0.000005959845,0.0002599103,0.00006004744,0.0001147507,0.0002126406],"domain_scores_gemma":[0.9994164,0.0000227664,0.00006190318,0.000361421,0.00003684171,0.0001006919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000491473,0.0002317711,0.5186572,0.009903171,0.0004432983,0.00003575229,0.08937827,0.001172708,0.00002073583,0.2119402,0.002378565,0.1657892],"study_design_scores_gemma":[0.001165337,0.0001765157,0.218574,0.00004643691,0.00008599694,0.00007361367,0.137855,0.4728453,0.00004767329,0.1651096,0.003336268,0.0006842946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855214,0.0001543205,0.001583836,0.0001307679,0.00004665186,0.0002726377,0.00002867305,0.0000670313,0.01219466],"genre_scores_gemma":[0.998513,0.00010211,0.001292352,0.00002197037,0.00001753733,0.000007090425,0.000002957029,0.00000736168,0.00003566372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4716725,"threshold_uncertainty_score":0.5074385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00482761047209612,"score_gpt":0.2250280210032061,"score_spread":0.2202004105311099,"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."}}