{"id":"W4311706555","doi":"10.1002/aaai.12068","title":"Search and learning for unsupervised text generation","year":2022,"lang":"en","type":"article","venue":"AI Magazine","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"DeepMind; Alberta Machine Intelligence Institute; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Computer science; Artificial intelligence; Heuristic; Task (project management); Sentence; Annotation; Machine learning; Function (biology); Component (thermodynamics); Unsupervised learning; Natural language processing; Resource (disambiguation)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001346014,0.000353053,0.0006473921,0.001033803,0.0005100503,0.0009705062,0.0009406055,0.0008150227,0.003880935],"category_scores_gemma":[0.005848308,0.0003287494,0.0007985419,0.001080765,0.0009578404,0.001775793,0.001104181,0.001267055,0.0009307784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017152,"about_ca_system_score_gemma":0.0009030044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001626256,"about_ca_topic_score_gemma":0.002586413,"domain_scores_codex":[0.9993203,0.0002959809,0.00003898583,0.0001682092,0.0001330963,0.00004352926],"domain_scores_gemma":[0.9970946,0.00209091,0.0001942544,0.0002793787,0.0002726764,0.00006822978],"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":[0.0001061296,0.000108067,0.001317579,0.0002405665,0.00006313423,0.0001104397,0.0001972113,0.5453834,0.005031321,0.175144,0.01336788,0.2589303],"study_design_scores_gemma":[0.000006852437,0.000008466731,0.00006829176,0.000006899348,0.000002619484,0.00001390746,0.000007659296,0.9580219,0.0006156364,0.04001963,0.001224276,0.000003779424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01160186,0.0003745969,0.9841339,0.0005035927,0.00003505498,0.00004728405,0.000146732,0.0006693826,0.002487568],"genre_scores_gemma":[0.4763709,0.0006139613,0.5103254,0.0004002299,0.000213147,0.0004026965,0.001176898,0.0004162844,0.01008048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003880935,"threshold_uncertainty_score":0.01298308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03918375269357233,"score_gpt":0.2721839684174112,"score_spread":0.2330002157238389,"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."}}