{"id":"W4388652381","doi":"","title":"Literary Natural Language Generation with Psychological Traits","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Natural language generation; Computer science; Natural (archaeology); Natural language; Natural language processing; Linguistics; Psychology; History; 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":[0.002408239,0.0003785193,0.0003542499,0.001174079,0.0006722289,0.004027802,0.0004818954,0.0008072513,0.00960257],"category_scores_gemma":[0.02881297,0.0004932287,0.0005284403,0.0008960856,0.001072637,0.002741107,0.001447574,0.001201617,0.001448488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007682212,"about_ca_system_score_gemma":0.000387261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006431279,"about_ca_topic_score_gemma":0.0004860059,"domain_scores_codex":[0.9980103,0.001227726,0.00006132937,0.0003998039,0.0002005252,0.0001004559],"domain_scores_gemma":[0.9725941,0.02162941,0.001456176,0.001384356,0.001954083,0.0009819118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00220787,0.001147419,0.1479531,0.001138749,0.0004992124,0.003560134,0.022931,0.05743493,0.05474874,0.3460838,0.01936597,0.342929],"study_design_scores_gemma":[0.0001505937,0.0004875234,0.08866044,0.0001471649,0.0002147858,0.001661965,0.005081654,0.6093442,0.01057365,0.2720487,0.01146794,0.0001613604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7360553,0.0004927454,0.2186826,0.002854394,0.0001764625,0.0001428529,0.0007461096,0.00145138,0.03939821],"genre_scores_gemma":[0.98941,0.0000583906,0.007112984,0.00005376825,0.00005788827,0.00003711441,0.0002717344,0.0001306004,0.002867413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00960257,"threshold_uncertainty_score":0.0321238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0259775689900038,"score_gpt":0.2548634877187326,"score_spread":0.2288859187287288,"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."}}