{"id":"W2179037780","doi":"10.3233/ao-140135","title":"Semantic Web and Big Data meets Applied Ontology","year":2014,"lang":"en","type":"article","venue":"Applied Ontology","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Coordination Office; National Institute of Standards and Technology","keywords":"Computer science; Ontology; Semantic Web; Information retrieval; Big data; World Wide Web; Data science; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007045492,0.0003573902,0.0007374413,0.0001982703,0.0002105624,0.0001072908,0.002718691,0.0003394805,0.00001516129],"category_scores_gemma":[0.0001166595,0.0003188167,0.00003754788,0.0002599107,0.0004079354,0.0001542306,0.001772887,0.0002813385,0.0001703988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002313439,"about_ca_system_score_gemma":0.0001003263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001517543,"about_ca_topic_score_gemma":0.0025059,"domain_scores_codex":[0.9970066,0.0001160617,0.0004608449,0.001377667,0.0002321128,0.0008067316],"domain_scores_gemma":[0.9964122,0.0006257964,0.0001928819,0.002560848,0.0000373371,0.0001709256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003133397,0.00007262681,0.00130607,0.00003888952,0.00006101831,0.00002263632,0.0003142767,0.000003460033,0.003515794,0.7250885,0.003391,0.2661544],"study_design_scores_gemma":[0.008633244,0.0006082686,0.08118188,0.00004245721,0.0002944438,0.001293406,0.0005588486,0.06655227,0.003838742,0.2245011,0.6095511,0.002944287],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.143062,0.001355744,0.6469353,0.01597723,0.00362546,0.001141186,0.00001713591,0.001662825,0.186223],"genre_scores_gemma":[0.970773,0.00007261215,0.02634815,0.002370489,0.0002556745,0.0000491937,0.00002616053,0.00001985787,0.00008490373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8277109,"threshold_uncertainty_score":0.9999264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04568034839592731,"score_gpt":0.2491437124384486,"score_spread":0.2034633640425212,"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."}}