{"id":"W4240269276","doi":"10.1007/978-0-387-39940-9_3796","title":"Text Databases","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Database; Computer science; Information retrieval","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","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.00115296,0.001451358,0.00221312,0.001051373,0.000136404,0.00005821102,0.001340184,0.0004654631,0.002017354],"category_scores_gemma":[0.0003599768,0.001430811,0.000454527,0.000182281,0.0003580131,0.0008222189,0.000564027,0.001040476,0.01881048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002723229,"about_ca_system_score_gemma":0.000608875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008288295,"about_ca_topic_score_gemma":0.0001963686,"domain_scores_codex":[0.9929894,0.000159763,0.002288621,0.0016296,0.002064615,0.0008680367],"domain_scores_gemma":[0.9918003,0.0004472951,0.002185134,0.004605077,0.0004423368,0.0005198763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001310831,0.0001891673,0.00006561859,0.001612384,0.0004525429,0.0005696315,0.0001003888,0.00002567487,0.0004367195,0.232703,0.7577378,0.005976033],"study_design_scores_gemma":[0.0006578621,0.0001191446,0.00002371241,0.003729065,0.0004967688,0.0001382992,0.00004629804,0.00003821907,0.00004573712,0.0001682427,0.9931672,0.001369414],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00002989914,0.01380896,0.0001285135,0.00001703696,0.002072788,0.00169728,0.07622973,0.0004609331,0.9055548],"genre_scores_gemma":[0.0004513727,0.006260607,0.001289266,0.00004426443,0.002918703,0.00006564979,0.03048979,0.0007402431,0.9577401],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2354295,"threshold_uncertainty_score":0.9998236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0308108654230772,"score_gpt":0.2658532420880608,"score_spread":0.2350423766649836,"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."}}