{"id":"W2339045699","doi":"","title":"RHYME ANALYZER: AN ANALYSIS TOOL FOR RAP LYRICS","year":2010,"lang":"de","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rhyme; Lyrics; Disk formatting; Linguistics; Face (sociological concept); Syllable; Natural language processing; Style (visual arts); Computer science; Speech recognition; Artificial intelligence; Art; Literature; Poetry; Philosophy","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":[0.001177858,0.002531786,0.00104706,0.005272949,0.0007417271,0.001905668,0.001652921,0.0008784303,0.05001983],"category_scores_gemma":[0.005272473,0.0009869039,0.0009800988,0.002506872,0.0004169082,0.002371316,0.001920259,0.001155188,0.0303129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003696959,"about_ca_system_score_gemma":0.0007736676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001256992,"about_ca_topic_score_gemma":0.00151793,"domain_scores_codex":[0.9989092,0.0001877157,0.0001875432,0.0002663074,0.0003734376,0.00007579526],"domain_scores_gemma":[0.9976076,0.001007918,0.0002307883,0.0004328222,0.0006054769,0.0001154168],"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":[0.000908262,0.0001728554,0.004047384,0.00143952,0.0001700246,0.0009892648,0.001387377,0.001530645,0.08604059,0.005953396,0.1341372,0.7632235],"study_design_scores_gemma":[0.0004101928,0.0006022467,0.02284136,0.0003860651,0.0002213738,0.004719013,0.001664524,0.1649247,0.2625799,0.01499805,0.5261832,0.0004694487],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01023322,0.0003276236,0.659864,0.00007973419,0.0001055166,0.0004336394,0.01974748,0.3021666,0.00704206],"genre_scores_gemma":[0.07022002,0.0003203908,0.8520603,0.0001040501,0.0001687203,0.001150248,0.02988073,0.03291626,0.01317942],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.05001983,"threshold_uncertainty_score":0.167333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01195315545738557,"score_gpt":0.2976526711350873,"score_spread":0.2856995156777017,"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."}}