{"id":"W1550275522","doi":"","title":"Rapid Application Development Using Agent Itinerary Patterns","year":2000,"lang":"en","type":"article","venue":"","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science; Task (project management); Variety (cybernetics); Distributed computing; Set (abstract data type); State (computer science); Mobile agent; Simple (philosophy); Ranging; Conjunction (astronomy); Artificial intelligence; Programming language; Telecommunications; Engineering; Systems engineering","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":[0.003643689,0.0009445992,0.000380601,0.001011588,0.0005702396,0.001814143,0.001973418,0.0009014884,0.004710493],"category_scores_gemma":[0.01345286,0.0009009629,0.001021822,0.0007748337,0.0006020571,0.003171869,0.002350037,0.001959226,0.003451012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005159795,"about_ca_system_score_gemma":0.001058476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000928337,"about_ca_topic_score_gemma":0.001172495,"domain_scores_codex":[0.9983763,0.0004095895,0.0002576158,0.0002753772,0.0005646506,0.0001164702],"domain_scores_gemma":[0.9938557,0.002315898,0.0004199411,0.002210186,0.0009111815,0.0002871675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004395657,0.0005162841,0.004615666,0.0007442419,0.0001220757,0.001278706,0.002750796,0.02206286,0.08753575,0.07154769,0.01984707,0.7885394],"study_design_scores_gemma":[0.0003757151,0.0008893909,0.003498676,0.0005071082,0.0001764716,0.002519493,0.0006098641,0.3005368,0.1763082,0.0712984,0.4430641,0.0002159153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01612167,0.0001129495,0.9599194,0.0002498025,0.00006997841,0.0005807647,0.0001953758,0.01522047,0.007529587],"genre_scores_gemma":[0.06069519,0.0003344381,0.9271014,0.000145515,0.00001998533,0.0009206443,0.0009489823,0.002440238,0.007393546],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004710493,"threshold_uncertainty_score":0.01926988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0553808240295366,"score_gpt":0.2443130616557401,"score_spread":0.1889322376262035,"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."}}