{"id":"W2095204883","doi":"10.1115/detc2006-99379","title":"A Multi-Agent System for Distributed, Internet Enabled Cutter/Workpiece Engagement Extractions","year":2006,"lang":"en","type":"article","venue":"","topic":"Injection Molding Process and Properties","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Distributed computing; Computer science; Computation; Scheduling (production processes); Overhead (engineering); Process (computing); The Internet; Multi-agent system; Engineering; Artificial intelligence; Algorithm; Operating system","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":[0.0006862329,0.0003541418,0.0004880904,0.0003666993,0.0008746964,0.001291101,0.001336723,0.000974696,0.003200245],"category_scores_gemma":[0.0009229634,0.00026008,0.0003445006,0.0002890616,0.0004304452,0.0009674417,0.001086783,0.0008210847,0.0008246691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005174382,"about_ca_system_score_gemma":0.001020189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001905159,"about_ca_topic_score_gemma":0.002205191,"domain_scores_codex":[0.9995403,0.0001337453,0.0000451222,0.00008086467,0.0001576939,0.00004234624],"domain_scores_gemma":[0.9996197,0.0001087967,0.00004467097,0.00006245344,0.00009724672,0.00006705882],"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":[0.0006960384,0.0006888668,0.002372572,0.0005220457,0.0001904776,0.001924698,0.0008102831,0.3689546,0.09609366,0.1011738,0.0142704,0.4123025],"study_design_scores_gemma":[0.0001267191,0.0002164478,0.000401482,0.00002537942,0.00004550578,0.0002330357,0.00005734667,0.9406161,0.01189785,0.006262071,0.04008149,0.00003667982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01542663,0.0002889381,0.9745282,0.0002287477,0.0001073388,0.0002703189,0.0000513964,0.003503765,0.005594678],"genre_scores_gemma":[0.3755207,0.000414687,0.6134587,0.0001353772,0.00007666383,0.0005997083,0.0001926075,0.0001439275,0.009457664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003200245,"threshold_uncertainty_score":0.01070583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02708096450560985,"score_gpt":0.2301579385324287,"score_spread":0.2030769740268189,"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."}}