{"id":"W2099605862","doi":"10.1007/978-3-540-27773-6_6","title":"Hyphenation Patterns for Ancient and Modern Greek","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Historical and Literary Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"McGill University","keywords":"Modern Greek; Computer science; Stress (linguistics); Linguistics; Ancient Greek; Consonant; Grammar; Greek language; Natural language processing; Word (group theory); Vowel; Artificial intelligence; Speech recognition; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.000592077,0.0002187625,0.0001973187,0.002256106,0.001117259,0.002205387,0.000442185,0.0004914457,0.01965305],"category_scores_gemma":[0.005578291,0.0001627152,0.0001689956,0.004035189,0.001653252,0.002586857,0.0008942433,0.000862524,0.001802967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006579442,"about_ca_system_score_gemma":0.0004152977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478702,"about_ca_topic_score_gemma":0.002117869,"domain_scores_codex":[0.999343,0.0002498322,0.0000814846,0.0001064841,0.0001439539,0.00007524624],"domain_scores_gemma":[0.9961717,0.002391466,0.000389767,0.0004583717,0.0004707742,0.0001180765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008102191,0.0001519407,0.0326568,0.0004030517,0.0000415201,0.00112588,0.09834078,0.0007930199,0.007965969,0.6016148,0.01386885,0.2422271],"study_design_scores_gemma":[0.0002021429,0.0003852228,0.2144517,0.0006387599,0.0001113024,0.008426028,0.07425588,0.0138591,0.007377722,0.3821194,0.2980421,0.000130781],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.7619413,0.002599078,0.01830511,0.001307922,0.0001487335,0.00008078938,0.001671507,0.0003540648,0.2135915],"genre_scores_gemma":[0.9779415,0.0003711903,0.005681991,0.00004814227,0.0000405821,0.00003536377,0.0008095925,0.0001446373,0.01492701],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01965305,"threshold_uncertainty_score":0.06574601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424494260381936,"score_gpt":0.2610588296448282,"score_spread":0.2368138870410089,"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."}}