{"id":"W4388296893","doi":"10.5267/j.uscm.2023.9.015","title":"Environmental education using SARITHA-Apps to enhance environmentally friendly supply chain efficiency and foster environmental knowledge towards sustainability","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Supply chain; Environmentally friendly; Environmental education; Business; Supply chain management; Environmental economics; Sustainability organizations; Marketing; Psychology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002231035,0.001234801,0.0007848399,0.002126892,0.00107788,0.0007302824,0.001264169,0.0002428643,0.001222432],"category_scores_gemma":[0.0001026215,0.001359389,0.0002910393,0.001651581,0.0004944518,0.001383832,0.004130917,0.0004231879,0.001185854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003142673,"about_ca_system_score_gemma":0.0001313514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007216264,"about_ca_topic_score_gemma":0.00006638485,"domain_scores_codex":[0.9925631,0.0001770933,0.001185699,0.00247677,0.001395384,0.00220198],"domain_scores_gemma":[0.9976355,0.0001210411,0.000420004,0.001530931,0.00005252215,0.0002400087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008192856,0.005902637,0.08917864,0.005362739,0.0008315938,0.0008779712,0.007445641,0.02554371,0.004659935,0.01746277,0.06342237,0.7784927],"study_design_scores_gemma":[0.003049947,0.0003744888,0.09636647,0.0004083725,0.0006565006,0.00002317569,0.1121292,0.05610379,0.0005952294,0.009134324,0.717002,0.004156441],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620197,0.001127286,0.007320789,0.007507173,0.001484924,0.009919272,0.0001245202,0.0008076426,0.009688701],"genre_scores_gemma":[0.9820085,0.000287498,0.001535906,0.003297014,0.0008642611,0.001267649,0.000641403,0.0002371517,0.009860607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7743363,"threshold_uncertainty_score":0.9996906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008708641242687288,"score_gpt":0.2491509804751333,"score_spread":0.240442339232446,"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."}}