{"id":"W1483126190","doi":"10.1007/978-0-387-34347-1_5","title":"A Distributed Agent System upon Semantic Web Technologies to Provide Biological Data","year":2006,"lang":"en","type":"book-chapter","venue":"Semantic web and beyond","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Biological data; Computer science; Biological database; Ontology; Semantic Web; World Wide Web; Data science; Bioinformatics; Biology","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":[0.0002652122,0.0005693685,0.000617839,0.0001207285,0.0001603025,0.0001171244,0.000780577,0.001020273,0.00001092875],"category_scores_gemma":[0.00003562824,0.0004522474,0.000128076,0.00005555137,0.0001860695,0.000006773801,0.001619873,0.0003315383,0.00007092368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003774159,"about_ca_system_score_gemma":0.0001373843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001170374,"about_ca_topic_score_gemma":0.0001249326,"domain_scores_codex":[0.9977237,0.0000203513,0.0006347488,0.0009129518,0.0002023833,0.0005058655],"domain_scores_gemma":[0.9980833,0.00002242965,0.000276305,0.001412183,0.00007582982,0.0001299298],"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":[0.0006026656,0.0003036815,0.0005149739,0.004279988,0.002069203,0.0005346034,0.00008477097,0.000199373,0.08838966,0.05600139,0.762751,0.08426861],"study_design_scores_gemma":[0.0007194363,0.0005539604,0.00004006116,0.0004977315,0.0002678303,0.0002112673,0.0001665653,0.005480302,0.0006649572,0.001621028,0.9886202,0.001156675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1873095,0.07460692,0.04038412,0.01226071,0.006143948,0.01580442,0.03573313,0.002640311,0.6251169],"genre_scores_gemma":[0.956866,0.001803619,0.00102107,0.0002766304,0.0005726882,0.00003629013,0.009506925,0.0000908381,0.02982591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7695565,"threshold_uncertainty_score":0.9997929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0163477411522335,"score_gpt":0.2233619560273125,"score_spread":0.207014214875079,"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."}}