{"id":"W3150089250","doi":"10.5267/j.uscm.2021.1.005","title":"The effect of logistics management, supply chain facilities and competitive storage costs on the use of warehouse financing of agricultural products","year":2021,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Warehouse; Nonprobability sampling; Supply chain; Java; Agriculture; Supply chain management; Sustainability; Operations management; Environmental economics; Marketing; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009929442,0.0001944401,0.0001428418,0.000620195,0.0002735477,0.001125583,0.0002656362,0.0002144389,0.00208894],"category_scores_gemma":[0.005181689,0.0001397045,0.0002296319,0.0009459078,0.0003954773,0.0007384894,0.0005696871,0.0003708445,0.0001187925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008273732,"about_ca_system_score_gemma":0.0009740517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00814888,"about_ca_topic_score_gemma":0.01255352,"domain_scores_codex":[0.9990553,0.0003978515,0.00007992479,0.00008169922,0.0002296708,0.0001556374],"domain_scores_gemma":[0.990227,0.004604335,0.003762512,0.0002329703,0.0005895558,0.0005836207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001291724,0.0001542788,0.9848697,0.00003640776,0.0000574029,0.0002839441,0.0006338969,0.0007792523,0.0008402456,0.0002360741,0.00007359693,0.01190607],"study_design_scores_gemma":[0.000002730186,0.0001496404,0.9952641,0.0000161943,0.00002871232,0.0001310281,0.002400381,0.001154189,0.0003623795,0.00007378124,0.0004088126,0.000008013901],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991413,0.00006395198,0.00007125465,0.00003153751,7.864089e-7,0.000003127941,0.00002402457,9.851369e-7,0.0006629056],"genre_scores_gemma":[0.9996619,0.00005815985,0.00007654774,0.000003503767,8.543191e-7,0.000001481264,0.00001937584,5.423618e-7,0.0001776393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00814888,"threshold_uncertainty_score":0.01620287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848274500078168,"score_gpt":0.2114690064458026,"score_spread":0.1929862614450209,"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."}}