{"id":"W2990863969","doi":"10.22259/2637-5885.0202005","title":"Visual Text: Encoding Challenges in Picasso’s Poetry","year":2019,"lang":"en","type":"article","venue":"Journal of Fine Arts","topic":"Digital Media and Visual Art","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"PICASSO; Poetry; Painting; Encoding (memory); Composition (language); Expression (computer science); Art; Visual arts; ENCODE; Computer science; Linguistics; Literature; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003959921,0.00008212897,0.0001989998,0.0002093285,0.0000136451,0.0000713983,0.000372882,0.00003404948,0.00002317353],"category_scores_gemma":[0.0001140833,0.00006471928,0.00006926509,0.0001588064,0.00001073025,0.0009149602,0.0001090807,0.0001724498,0.000137266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003159785,"about_ca_system_score_gemma":0.00005367108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001540144,"about_ca_topic_score_gemma":0.000008903505,"domain_scores_codex":[0.9990253,0.00002420096,0.0003184267,0.0001255665,0.0002936385,0.0002128994],"domain_scores_gemma":[0.9993857,0.0001353184,0.0001654018,0.000140263,0.00006305594,0.0001102627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006278158,0.001007335,0.04327863,0.00009456002,0.00005065213,0.0009174994,0.004552249,0.0001010157,0.01292453,0.06205727,0.002301444,0.8726521],"study_design_scores_gemma":[0.01070285,0.01008263,0.6602941,0.002762529,0.00003404259,0.003808472,0.002144531,0.02548684,0.03350371,0.03526914,0.2138294,0.00208169],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715265,0.0006618478,0.0008381162,0.004645994,0.001039966,0.00005388038,1.81077e-7,0.00001555011,0.02121793],"genre_scores_gemma":[0.9982058,0.00007307305,0.001235117,0.0001296278,0.0001632709,4.575198e-7,7.907295e-8,0.000004678716,0.0001879005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8705704,"threshold_uncertainty_score":0.2639175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04535386072694225,"score_gpt":0.3023206963869034,"score_spread":0.2569668356599611,"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."}}