{"id":"W4205402178","doi":"10.18280/ts.380630","title":"Evaluation of Logistics Service Quality: Sentiment Analysis of Comment Text Based on Multi-Level Graph Neural Network","year":2021,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministry of Education of the People's Republic of China","keywords":"Computer science; Graph; Sentiment analysis; Pillar; Service quality; Quality of service; Artificial neural network; Service (business); Artificial intelligence; Data mining; Natural language processing; Theoretical computer science; Computer network; Engineering","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":[0.0005211898,0.0006033484,0.0003393154,0.001249621,0.0002163385,0.0004514444,0.0003355027,0.0004481609,0.001031974],"category_scores_gemma":[0.001929393,0.00008953903,0.0004454109,0.0007177435,0.0002225042,0.0006662028,0.0002800574,0.0003916077,0.0003430195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007018222,"about_ca_system_score_gemma":0.0002321663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006259913,"about_ca_topic_score_gemma":0.006378144,"domain_scores_codex":[0.9996456,0.00009097518,0.00002837525,0.0000864476,0.0001009635,0.00004766938],"domain_scores_gemma":[0.9991967,0.0002609208,0.0001086342,0.00002898243,0.0003636662,0.00004107575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00236458,0.0007233291,0.09445889,0.0005653901,0.0004253865,0.000837294,0.001057661,0.1498485,0.08025736,0.00175114,0.01063768,0.6570727],"study_design_scores_gemma":[0.000007096563,0.00009433837,0.01178989,0.000007068404,0.00003823108,0.00002692572,0.0001423755,0.9821857,0.004997368,0.0003347716,0.0003658845,0.00001039692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8908814,0.0002899314,0.1018757,0.000457337,0.0001710635,0.0001540461,0.0007486163,0.0008420224,0.004579887],"genre_scores_gemma":[0.9897295,0.00008553223,0.008505698,0.00003663826,0.00003247409,0.00003099507,0.0005213749,0.00001320209,0.001044624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006259913,"threshold_uncertainty_score":0.01244694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1903598385226112,"score_gpt":0.3601073663493223,"score_spread":0.1697475278267112,"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."}}