{"id":"W3176071257","doi":"10.1109/hora52670.2021.9461354","title":"Sentiment Analysis of Meeting Room","year":2021,"lang":"en","type":"article","venue":"2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Sentiment analysis; Normalization (sociology); Artificial neural network; Big data; Artificial intelligence; Data modeling; Speech recognition; Machine learning; Data mining; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002398294,0.0002293815,0.0004061842,0.0008718416,0.0003397647,0.0004911283,0.0005541816,0.00008023888,0.0008173863],"category_scores_gemma":[0.0000218904,0.0002398558,0.0002557093,0.001378818,0.00004869531,0.0005058164,0.0003121321,0.000159909,0.00002334615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009167119,"about_ca_system_score_gemma":0.00004343758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001614462,"about_ca_topic_score_gemma":0.00001569799,"domain_scores_codex":[0.9976389,0.0001216752,0.0007891491,0.0007398461,0.0005278522,0.0001825146],"domain_scores_gemma":[0.9976236,0.0001892225,0.0005489354,0.0005917581,0.0009443049,0.0001021642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005027184,0.0003202798,0.002196929,0.000009413331,0.00151656,0.000004030931,0.0002266019,0.9422275,0.0003029385,0.0474439,0.001459751,0.004287116],"study_design_scores_gemma":[0.0003232362,0.00003201486,0.0009447504,0.00006556381,0.0002937879,0.00000797055,0.0001455193,0.9895658,0.001962858,0.0001075975,0.006319902,0.0002309805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001503167,0.0001053422,0.9932814,0.001474635,0.001278806,0.000187172,0.000009254406,0.00006283521,0.002097409],"genre_scores_gemma":[0.6706518,0.0004357023,0.3193839,0.0009791086,0.0006429097,0.0001785483,0.001374878,0.0000438046,0.006309329],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6738974,"threshold_uncertainty_score":0.9781034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03038711447665572,"score_gpt":0.3302187355578874,"score_spread":0.2998316210812317,"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."}}