{"id":"W4239308454","doi":"10.1007/978-0-387-39940-9_3991","title":"Web Content Extraction","year":2009,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Database Systems","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Extraction (chemistry); Web content; World Wide Web; Chromatography; Chemistry; The Internet","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":[0.0005564893,0.0003965495,0.0007401846,0.0004020239,0.00007556236,0.0001018229,0.001198205,0.0002248943,0.00006461974],"category_scores_gemma":[0.00006410446,0.0003647264,0.0002336102,0.0001029364,0.00005001871,0.0007128481,0.0002658286,0.0003712913,0.000345813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000065724,"about_ca_system_score_gemma":0.0002232043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002060888,"about_ca_topic_score_gemma":0.00002695291,"domain_scores_codex":[0.9973033,0.00005688448,0.0008707987,0.0007615965,0.0007340349,0.000273398],"domain_scores_gemma":[0.9966665,0.000134425,0.0008262279,0.002017315,0.0001888623,0.0001666578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002387574,0.0002165407,0.00008945498,0.0007808945,0.0007069056,0.0005673515,0.0003329007,0.00007494869,0.001265982,0.5862189,0.2532786,0.1564437],"study_design_scores_gemma":[0.0002348578,0.00007858943,0.0000187794,0.0008018095,0.0001259887,0.00005335205,0.00002948936,0.002785692,0.00002346299,0.0001219894,0.9952742,0.0004517486],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00003757589,0.003980305,0.03476185,0.0001250324,0.002096512,0.0003460479,0.001481539,0.0002202824,0.9569508],"genre_scores_gemma":[0.002691436,0.005945507,0.008021827,0.00006297808,0.001167226,0.00001953828,0.001771022,0.00005432122,0.9802662],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7419957,"threshold_uncertainty_score":0.9998805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03516957540448347,"score_gpt":0.250518595400411,"score_spread":0.2153490199959276,"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."}}