{"id":"W4212856284","doi":"10.5220/0010812100003116","title":"Analysing the Sentiments in Online Reviews with Special Focus on Automobile Market","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 14th International Conference on Agents and Artificial Intelligence","topic":"Technology and Data Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Focus (optics); Computer science; Data science; Automotive industry; Engineering; Aerospace engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005436886,0.0001296642,0.0001750449,0.0001966524,0.0002586659,0.0001306901,0.001650368,0.00002615859,0.000425216],"category_scores_gemma":[0.0000844275,0.00007625617,0.00006400558,0.0005972476,0.0001355826,0.0001903565,0.0006170458,0.0003219312,0.000006600963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000550888,"about_ca_system_score_gemma":0.0000259915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004269424,"about_ca_topic_score_gemma":0.00004846227,"domain_scores_codex":[0.9986353,0.00003462019,0.0003601445,0.0003559547,0.0004603553,0.0001536078],"domain_scores_gemma":[0.9993261,0.00003899025,0.0003039484,0.0002008416,0.0001034551,0.00002664129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000171553,0.0005443008,0.004756647,0.000009408566,0.00008512371,0.000005083441,0.0008362941,0.0003018715,0.0005604738,0.8236493,0.002184962,0.166895],"study_design_scores_gemma":[0.0003161746,0.0009921528,0.01777228,0.0005388628,0.0001090548,0.00004448376,0.004849055,0.6640363,0.02587529,0.2637942,0.02090225,0.000769912],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8935781,0.0001154949,0.008644192,0.05422412,0.001672257,0.001426078,0.0001603818,0.0001150039,0.04006442],"genre_scores_gemma":[0.9984578,0.00009139157,0.000523382,0.0004265458,0.00007552659,0.00003211875,0.000002771877,0.000004032909,0.0003864451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6637344,"threshold_uncertainty_score":0.4655817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06808432505563496,"score_gpt":0.3129416896297311,"score_spread":0.2448573645740962,"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."}}