{"id":"W1594494575","doi":"10.1007/3-540-39963-1_47","title":"Automatic Semantic Header Generator","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Search engine indexing; Computer science; Header; Information retrieval; Automatic indexing; Resource (disambiguation); Information extraction; The Internet; Context (archaeology); Generator (circuit theory); Data mining; World Wide Web","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":[0.001115215,0.001765506,0.001137668,0.003682377,0.0008905961,0.00214017,0.001709764,0.001321098,0.04102559],"category_scores_gemma":[0.004048554,0.001064258,0.001374812,0.002171681,0.0006129807,0.003754201,0.002820245,0.00164738,0.018387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008664907,"about_ca_system_score_gemma":0.001334361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008739978,"about_ca_topic_score_gemma":0.0008968154,"domain_scores_codex":[0.9992654,0.0001104618,0.0000679257,0.0002076884,0.0002686851,0.00007984041],"domain_scores_gemma":[0.9981028,0.0007135973,0.00008507095,0.0005587352,0.0004605287,0.00007924504],"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":[0.0009210099,0.00032589,0.001558003,0.0007414097,0.00009473815,0.001050967,0.000278397,0.004946862,0.05224878,0.04468542,0.1929155,0.700233],"study_design_scores_gemma":[0.0003347685,0.0001867339,0.001393102,0.0002871589,0.0002892149,0.001528119,0.0003109097,0.2634449,0.3657306,0.09736197,0.2689678,0.0001648334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01308596,0.0003700082,0.7585823,0.0004309953,0.00066514,0.0004386882,0.005870244,0.2072658,0.01329083],"genre_scores_gemma":[0.1211175,0.0005162199,0.7838978,0.0006698573,0.0002518895,0.0005431024,0.03680677,0.02865686,0.02754001],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04102559,"threshold_uncertainty_score":0.1372443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005951519168582,"score_gpt":0.2453746573692003,"score_spread":0.2253151421775145,"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."}}