{"id":"W1965370068","doi":"10.1002/spe.621","title":"Making XML document markup international","year":2004,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; University of Toronto","funders":"","keywords":"Computer science; SGML; World Wide Web; XML validation; Markup language; Efficient XML Interchange; XML; Document Structure Description; XML Schema Editor; RuleML; XML Schema (W3C); Streaming XML; Document type definition; Information retrieval; Programming language","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":[0.01131602,0.001274712,0.0008736453,0.003207497,0.001601713,0.008064398,0.002660922,0.002350523,0.01062441],"category_scores_gemma":[0.02636718,0.001069841,0.001518243,0.003899143,0.003000045,0.01248936,0.004902657,0.005380465,0.01081902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001019944,"about_ca_system_score_gemma":0.002203786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001062768,"about_ca_topic_score_gemma":0.0006138155,"domain_scores_codex":[0.9896667,0.003663733,0.001984554,0.001378675,0.003013831,0.0002924881],"domain_scores_gemma":[0.9817655,0.006271259,0.001031741,0.00659543,0.003906155,0.0004298882],"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":[0.0001687555,0.0001073291,0.0005926806,0.0006054528,0.00006912232,0.0005706335,0.004320518,0.002862617,0.01442001,0.371037,0.0622558,0.54299],"study_design_scores_gemma":[0.00003380713,0.00004757091,0.0002534203,0.0003097925,0.00005137935,0.000576688,0.0005439457,0.006658816,0.0245434,0.06136573,0.9055519,0.00006349818],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001598541,0.0007646828,0.9650563,0.001753934,0.001139815,0.0002642178,0.0004402372,0.00887593,0.0201063],"genre_scores_gemma":[0.02711261,0.002425781,0.9404869,0.00119139,0.0006833478,0.000423714,0.003130218,0.003980178,0.02056589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01131602,"threshold_uncertainty_score":0.05984551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285094262741164,"score_gpt":0.3258010483175628,"score_spread":0.3029501056901511,"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."}}