{"id":"W2103251029","doi":"","title":"Prior versus Contextual Emotion of a Word in a Sentence","year":2012,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Sentence; Computer science; Natural language processing; Word (group theory); Task (project management); Context (archaeology); Focus (optics); Artificial intelligence; Representation (politics); Set (abstract data type); Affect (linguistics); Function (biology); Interpretation (philosophy); Linguistics; Psychology; Communication","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":[0.0008717307,0.000357281,0.0003799698,0.001042383,0.0003850624,0.001596519,0.0002544342,0.0006832897,0.003182671],"category_scores_gemma":[0.004193471,0.0001132588,0.000321144,0.0006668713,0.0008999514,0.001800377,0.0006229162,0.0006145876,0.0009925389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003262199,"about_ca_system_score_gemma":0.000134317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003341948,"about_ca_topic_score_gemma":0.0007000256,"domain_scores_codex":[0.999267,0.000265175,0.00009367479,0.0001681648,0.0001423561,0.00006366512],"domain_scores_gemma":[0.9977028,0.001307122,0.0003032001,0.0001875118,0.0003895049,0.0001098943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004128951,0.0003426824,0.07862598,0.001376,0.0003841966,0.001219157,0.005516736,0.002761034,0.4230006,0.03903277,0.01025692,0.4333551],"study_design_scores_gemma":[0.000146032,0.002895442,0.6085744,0.000961092,0.001323274,0.006249605,0.007213148,0.1269288,0.08855044,0.08290474,0.07376006,0.0004930028],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8358905,0.001907565,0.1223611,0.001376245,0.0006754534,0.000213572,0.002522672,0.0007536219,0.03429923],"genre_scores_gemma":[0.9620793,0.0003724042,0.0340482,0.0001908484,0.0002861373,0.00008408938,0.001053501,0.00009028859,0.001795266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003182671,"threshold_uncertainty_score":0.01064712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04573831548744062,"score_gpt":0.2933397794791885,"score_spread":0.2476014639917479,"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."}}