{"id":"W1655544561","doi":"","title":"Collaborative And Proactive Data Agent For Distributed Design Environments","year":2003,"lang":"en","type":"article","venue":"NPARC","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; National Research Council Canada","funders":"","keywords":"Computer science; Workflow; Teamwork; Consistency (knowledge bases); Multidisciplinary approach; Concurrent engineering; Collaborative software; Data management; Collaborative engineering; Data consistency; Software engineering; Systems engineering; Knowledge management; Database; Work in process; Engineering; Scheduling (production processes); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00860322,0.0003775542,0.0007470997,0.001027334,0.00211358,0.004879158,0.001432406,0.002487466,0.06929981],"category_scores_gemma":[0.03541278,0.0005954996,0.0003654066,0.0009026501,0.001070008,0.005146428,0.002531719,0.001742033,0.02752739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008629202,"about_ca_system_score_gemma":0.00240549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000683617,"about_ca_topic_score_gemma":0.001850954,"domain_scores_codex":[0.9940829,0.001870395,0.0003553285,0.000581206,0.002881277,0.000228947],"domain_scores_gemma":[0.970603,0.00673203,0.001225131,0.007900765,0.01125744,0.002281715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003940627,0.000238149,0.003592443,0.0006946282,0.00005566061,0.0006787346,0.001077896,0.002261998,0.007992461,0.09868699,0.471147,0.4131799],"study_design_scores_gemma":[0.0001182223,0.0001512838,0.002209247,0.00016536,0.0000431988,0.0005334094,0.0004130005,0.01371677,0.00612078,0.0466927,0.9297731,0.00006303999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03523147,0.004433407,0.5282115,0.05474437,0.02453187,0.001742105,0.001321433,0.01299026,0.3367936],"genre_scores_gemma":[0.239232,0.002983496,0.1349647,0.002621888,0.00499882,0.0007528015,0.001998836,0.002164667,0.6102828],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06929981,"threshold_uncertainty_score":0.231831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02780859555691767,"score_gpt":0.2523629597208798,"score_spread":0.2245543641639621,"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."}}