{"id":"W4280533913","doi":"10.3390/su14106003","title":"Inventory Models in a Sustainable Supply Chain: A Bibliometric Analysis","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scopus; Supply chain; China; Sustainability; Bibliometrics; Sustainable development; Business; Citation; Consumption (sociology); Publication; Environmental economics; Production (economics); Per capita; Agriculture; Regional science; Agricultural economics; Marketing; Library science; Economics; Political science; Computer science; Geography; Social science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008286067,0.0007953433,0.001724036,0.1016477,0.001683911,0.01013051,0.001163933,0.001028602,0.003934766],"category_scores_gemma":[0.04019488,0.0004052748,0.002298947,0.1670467,0.0009072635,0.008166848,0.002833111,0.0005681802,0.0007083575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004122945,"about_ca_system_score_gemma":0.004017373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008249351,"about_ca_topic_score_gemma":0.005164881,"domain_scores_codex":[0.9876896,0.003596772,0.001329803,0.0006541703,0.00625951,0.0004701006],"domain_scores_gemma":[0.9735367,0.01770757,0.002888682,0.001533399,0.003930584,0.0004031137],"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":[0.0003556769,0.0007584052,0.2516976,0.009223135,0.002717802,0.001027311,0.004552904,0.08376955,0.001716986,0.06814764,0.02416872,0.5518643],"study_design_scores_gemma":[0.0001451784,0.0006670105,0.2988203,0.005344309,0.003299529,0.002182883,0.02011429,0.4338572,0.004152036,0.1051086,0.1258225,0.0004861484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7231678,0.04436585,0.07051518,0.006523351,0.0004872278,0.001169726,0.02097194,0.001175399,0.1316235],"genre_scores_gemma":[0.9447433,0.01733804,0.02758235,0.0001027427,0.0002635389,0.0004315632,0.006950538,0.00007347583,0.002514495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8983523,"threshold_uncertainty_score":0.04382145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389747655077909,"score_gpt":0.2371571648879904,"score_spread":0.2232596883372113,"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."}}