{"id":"W1927326449","doi":"10.1109/hicss.1998.649223","title":"Using metadata to query passive data sources","year":2002,"lang":"en","type":"article","venue":"","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Metadata; Information retrieval; World Wide Web; The Internet; Metadata repository; Popularity; Data element; Data extraction; Data management; Database","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":[0.01867134,0.0008297596,0.001196362,0.01005416,0.002344287,0.009000021,0.003301313,0.002121519,0.001639072],"category_scores_gemma":[0.05819205,0.0009520815,0.0012284,0.009780223,0.002306015,0.01625089,0.006875209,0.001841449,0.001000336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001812523,"about_ca_system_score_gemma":0.002900026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00427069,"about_ca_topic_score_gemma":0.005733453,"domain_scores_codex":[0.9884877,0.004008878,0.001567988,0.001324738,0.004261743,0.0003490781],"domain_scores_gemma":[0.9434242,0.02750448,0.004462918,0.01565088,0.007932181,0.001025409],"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":[0.001200747,0.0006686611,0.04483775,0.002596926,0.0005084875,0.003690696,0.02207138,0.01364224,0.05312059,0.2799054,0.02120257,0.5565546],"study_design_scores_gemma":[0.0004439148,0.0006384714,0.01059004,0.001196543,0.0005198593,0.004374113,0.0107602,0.2204638,0.1157544,0.3034065,0.3312926,0.0005594141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05178977,0.001234147,0.9272438,0.003225757,0.0001553576,0.001003032,0.0018685,0.004703095,0.008776497],"genre_scores_gemma":[0.2962257,0.001140062,0.6883512,0.0008076582,0.0001804861,0.000943713,0.005924734,0.0007925529,0.005633888],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01867134,"threshold_uncertainty_score":0.09874469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2351388666537689,"score_gpt":0.3190759787592714,"score_spread":0.08393711210550248,"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."}}