{"id":"W7097026846","doi":"","title":"Schema Management","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"IBM; Schema (genetic algorithms); Data management; Data integration; Conceptual schema; Context (archaeology); Information system; Management system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01036425,0.001260199,0.001373883,0.008401629,0.002285614,0.01263452,0.005033906,0.001965271,0.04852917],"category_scores_gemma":[0.02249832,0.001141092,0.002009826,0.01053298,0.001072846,0.01143546,0.008632022,0.004121693,0.03932816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002192586,"about_ca_system_score_gemma":0.005174582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004312683,"about_ca_topic_score_gemma":0.003489523,"domain_scores_codex":[0.9929986,0.001108893,0.001370669,0.001166776,0.00287854,0.0004765043],"domain_scores_gemma":[0.9832302,0.002030218,0.001030707,0.007885827,0.004803459,0.001019497],"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":[0.0003429888,0.0002558716,0.004271211,0.001122346,0.00024809,0.0006060298,0.002307004,0.002091402,0.009772914,0.1400453,0.4642063,0.3747306],"study_design_scores_gemma":[0.00003032277,0.00002436004,0.0005221429,0.0001512072,0.00004806591,0.0003948769,0.0002601972,0.002893561,0.004437627,0.01470635,0.9764891,0.00004214889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00777416,0.005263988,0.6125345,0.004955169,0.002420442,0.003078448,0.05861835,0.1104174,0.1949376],"genre_scores_gemma":[0.06292243,0.006947549,0.5218473,0.006300241,0.001082399,0.001804917,0.2342642,0.02010836,0.1447226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04852917,"threshold_uncertainty_score":0.1623462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01877771089336534,"score_gpt":0.207563864195598,"score_spread":0.1887861533022326,"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."}}