{"id":"W2014347812","doi":"10.1108/02640470710741331","title":"Building interoperable Canadian architecture collections: initial metadata assessment","year":2007,"lang":"en","type":"article","venue":"The Electronic Library","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Metadata; Interoperability; Architecture; Computer science; Collections management; Normalization (sociology); World Wide Web; Information retrieval; Database; Archaeology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02958715,0.0009591486,0.0008146709,0.02782362,0.01356927,0.007295854,0.003606547,0.0007735611,0.006148765],"category_scores_gemma":[0.07476948,0.0006433761,0.000836987,0.03298228,0.002792164,0.006792627,0.0078983,0.001051895,0.00097417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08109479,"about_ca_system_score_gemma":0.1352108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9426966,"about_ca_topic_score_gemma":0.9697452,"domain_scores_codex":[0.9655355,0.003827259,0.002362472,0.001592855,0.02454992,0.002131994],"domain_scores_gemma":[0.9024727,0.005433776,0.002936731,0.004330069,0.08230279,0.002523925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005656927,0.0005389066,0.287819,0.002134039,0.0001412106,0.0007308288,0.05507561,0.005098367,0.007657589,0.03603311,0.03533357,0.568872],"study_design_scores_gemma":[0.0000981267,0.00058546,0.5269931,0.001823486,0.0003763314,0.0005043527,0.1390919,0.01306113,0.02113731,0.005039361,0.2907909,0.0004984825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6980025,0.003918991,0.06155618,0.004757655,0.0001825324,0.01744598,0.03390504,0.001921468,0.1783096],"genre_scores_gemma":[0.78811,0.002581917,0.1674981,0.0003985436,0.00004598016,0.004643006,0.01920925,0.0003178555,0.01719536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08109479,"threshold_uncertainty_score":0.5883867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0159717583595294,"score_gpt":0.225805204015898,"score_spread":0.2098334456563686,"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."}}