{"id":"W1602711325","doi":"10.48550/arxiv.1405.0603","title":"Extracting Family Relationship Networks from Novels","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Topic Modeling","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003722676,0.00028784,0.0003037959,0.0001638467,0.000208503,0.0002006141,0.001962239,0.0004472083,0.00001256583],"category_scores_gemma":[0.00009608419,0.0003611657,0.0001795788,0.0003102418,0.00004324243,0.0004344023,0.001889259,0.001112103,0.00007882313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001737905,"about_ca_system_score_gemma":0.0001227875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005019901,"about_ca_topic_score_gemma":0.00003063169,"domain_scores_codex":[0.9978155,0.0001816391,0.0002669193,0.001274624,0.0001042726,0.0003570825],"domain_scores_gemma":[0.9970704,0.0005916524,0.0003501964,0.001723958,0.0001079583,0.0001558715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003860741,0.00001765573,0.009402139,0.00000943345,0.00002871738,0.00005299004,0.00011161,0.8836612,0.000009710358,0.1051864,0.0001073599,0.001408887],"study_design_scores_gemma":[0.0002067887,0.000006924963,0.009989784,0.00009055949,0.00003385139,0.000001045702,0.00002611063,0.929499,0.000005256308,0.05943447,0.0003588437,0.0003474153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.251212,0.00007414029,0.7443088,0.00006304813,0.001003741,0.0001256834,0.000003597709,0.0002794643,0.002929465],"genre_scores_gemma":[0.9790977,0.00002716867,0.01968628,0.0001796068,0.0003385449,5.99206e-7,0.00001744209,0.00001930934,0.0006333037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7278857,"threshold_uncertainty_score":0.999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1380578163277354,"score_gpt":0.1957076496235965,"score_spread":0.05764983329586115,"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."}}