{"id":"W147081156","doi":"10.1007/978-3-540-31849-1_88","title":"Address Extraction: Extraction of Location-Based Information from the Web","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Information retrieval; Information extraction; Precision and recall; Graph; Data mining; Matching (statistics); Ontology; Theoretical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002745939,0.001161411,0.001037241,0.006268358,0.000570056,0.001884279,0.001155913,0.001161866,0.005803302],"category_scores_gemma":[0.001754413,0.0005161311,0.001050935,0.006949588,0.0002542904,0.001766048,0.001380353,0.0005485163,0.0126173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002931394,"about_ca_system_score_gemma":0.0007678311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001839413,"about_ca_topic_score_gemma":0.002273255,"domain_scores_codex":[0.9996504,0.00004128287,0.00005205069,0.00009253738,0.0001210354,0.00004267688],"domain_scores_gemma":[0.9994382,0.0001920079,0.00007392326,0.0001123182,0.0001525886,0.00003098336],"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":[0.000280918,0.0001725022,0.005230605,0.001097015,0.0001245715,0.001280606,0.0003607061,0.002950421,0.03906194,0.004081594,0.04177001,0.9035891],"study_design_scores_gemma":[0.0002336668,0.000409185,0.02884401,0.0007910351,0.0009864297,0.005963924,0.001623397,0.2064897,0.2965639,0.05634104,0.4014608,0.0002929106],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05737551,0.005896495,0.8473393,0.001013973,0.0004734469,0.0004333738,0.03151768,0.03731094,0.01863925],"genre_scores_gemma":[0.2083006,0.005111575,0.6909257,0.0005042925,0.000404276,0.0003961838,0.06794666,0.001585965,0.02482472],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006268358,"threshold_uncertainty_score":0.01941401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151380279718067,"score_gpt":0.2436334765019314,"score_spread":0.2321196737047508,"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."}}