{"id":"W4206294659","doi":"10.1353/phx.2014.0014","title":"Exemplary Traits: Reading Characterization in Roman Poetry by J. Mira Seo","year":2014,"lang":"en","type":"article","venue":"Phoenix","topic":"Classical Antiquity Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Poetry; Reading (process); Mythology; Variety (cybernetics); Elegy; Literature; Order (exchange); Aside; History; Art; Aesthetics; Art history; Philosophy; Computer science; Linguistics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003951261,0.00008322301,0.000151823,0.0000501553,0.0002481568,0.00005031583,0.0001494671,0.0000699101,0.00008086115],"category_scores_gemma":[0.0003237993,0.00008359088,0.00003355076,0.0002730802,0.0001201436,0.0002090034,0.00004583596,0.000108708,0.00004857614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007197815,"about_ca_system_score_gemma":0.00001834609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004157915,"about_ca_topic_score_gemma":0.00158719,"domain_scores_codex":[0.998998,0.0001463507,0.0001568855,0.0001954817,0.0002201337,0.0002830806],"domain_scores_gemma":[0.999661,0.0001231545,0.00005414414,0.00007074947,0.00002309369,0.00006780212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000716185,0.0005743412,0.09774046,0.00009365117,0.00005470747,0.00001564939,0.1138381,0.000001361516,0.4220759,0.04246638,0.07212532,0.2509425],"study_design_scores_gemma":[0.0002560198,0.0000326276,0.1671695,0.00004547802,0.000007435263,4.622712e-7,0.0009657543,0.0000635061,0.001369983,0.0007242823,0.8291629,0.0002020419],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9608204,0.00002742706,0.0002736453,0.009905265,0.0001894316,0.0001412095,0.00002094028,0.0001021133,0.0285196],"genre_scores_gemma":[0.99573,0.00005633954,0.00005122164,0.0006949457,0.0002134521,0.00001110753,0.00002714901,0.000009113218,0.003206666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7570376,"threshold_uncertainty_score":0.3408737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01561417582188106,"score_gpt":0.2797369903890409,"score_spread":0.2641228145671599,"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."}}