{"id":"W4387297413","doi":"10.2139/ssrn.4568024","title":"Interplay Between Amazon Store and Logistics","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Amazon rainforest; Business; Computer science; Biology","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":[0.0009106229,0.0001302299,0.0002325693,0.0006650637,0.001800595,0.01124627,0.0005573751,0.00160445,0.05318241],"category_scores_gemma":[0.004706514,0.0002568298,0.0002514276,0.001519118,0.00239837,0.006198527,0.002216454,0.001273488,0.003638489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003639763,"about_ca_system_score_gemma":0.002750829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03822783,"about_ca_topic_score_gemma":0.04163352,"domain_scores_codex":[0.9990103,0.0003642642,0.00003898675,0.0001427932,0.0002645913,0.000179081],"domain_scores_gemma":[0.9968778,0.001378785,0.0004039515,0.0002734798,0.0005977975,0.0004682067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003332867,0.0001744312,0.01917633,0.000161902,0.0000625139,0.0007222121,0.006144089,0.001232101,0.00126206,0.9072945,0.03082107,0.03261549],"study_design_scores_gemma":[0.00009980641,0.0001379868,0.04687911,0.0002962467,0.0001327674,0.0008487598,0.04370597,0.007630593,0.001571154,0.353677,0.5448752,0.0001453402],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2356657,0.001628667,0.003861322,0.02166827,0.0001215744,0.00002907584,0.0004991833,0.00012705,0.7363991],"genre_scores_gemma":[0.9709699,0.0004787939,0.0004650897,0.0008723398,0.00008397322,0.000009286717,0.0001001864,0.00005244037,0.026968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05318241,"threshold_uncertainty_score":0.1779129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01467253975269905,"score_gpt":0.2569141589906001,"score_spread":0.242241619237901,"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."}}