{"id":"W6949396090","doi":"10.5281/zenodo.14167444","title":"Pronoun Generation for Text Summarization and Question Answering","year":2006,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Question answering; Automatic summarization; Pronoun; Natural language; Corpus linguistics","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":[0.002621809,0.001329518,0.001352234,0.003521931,0.001363494,0.00202233,0.001623857,0.001508737,0.01784298],"category_scores_gemma":[0.008728143,0.0005992656,0.0009924343,0.002961718,0.000522839,0.00324324,0.001721613,0.001212435,0.01338869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006736504,"about_ca_system_score_gemma":0.001022304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001870642,"about_ca_topic_score_gemma":0.00302579,"domain_scores_codex":[0.9976457,0.001190764,0.0001720394,0.0004788004,0.0003372229,0.0001753161],"domain_scores_gemma":[0.9960915,0.002067122,0.0002033205,0.0005950812,0.0009239535,0.0001190291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003839078,0.0001627116,0.0007370857,0.0009841344,0.0001165765,0.0002547145,0.0006079088,0.008329427,0.02768374,0.01685665,0.08603294,0.8578504],"study_design_scores_gemma":[0.0002036446,0.0003717172,0.001841227,0.0001937664,0.0002479888,0.0005769933,0.001020294,0.5834906,0.08494214,0.130824,0.1961749,0.0001126474],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0124548,0.003290141,0.9435192,0.001437853,0.000825544,0.0005966864,0.004831112,0.02542862,0.007616017],"genre_scores_gemma":[0.150002,0.00162624,0.8136398,0.00034692,0.0007599369,0.0005987185,0.01823536,0.001646532,0.01314458],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01784298,"threshold_uncertainty_score":0.05969071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692050918953954,"score_gpt":0.2347959751202338,"score_spread":0.2178754659306942,"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."}}