{"id":"W2113156330","doi":"10.1109/ism.2009.124","title":"Vision System Development through Separation of Management and Processing","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Abstraction; Scope (computer science); Reusability; Task (project management); Machine vision; Management system; Artificial intelligence; Abstraction layer; Data management; Software engineering; Human–computer interaction; Risk analysis (engineering); Data science; Systems engineering; Database; Engineering; Software; Operations management","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":[0.004498988,0.0007819292,0.0007505085,0.001100876,0.000833563,0.004655819,0.002878166,0.0009749955,0.002861819],"category_scores_gemma":[0.007193897,0.0009858734,0.001303197,0.0006477988,0.001887215,0.00533976,0.003445117,0.003170234,0.001374537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076042,"about_ca_system_score_gemma":0.004471822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004497949,"about_ca_topic_score_gemma":0.003386922,"domain_scores_codex":[0.9969855,0.000659415,0.0002356042,0.0006046748,0.001174214,0.0003406509],"domain_scores_gemma":[0.9957586,0.001282189,0.0003083958,0.001414903,0.0009696515,0.0002662435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002316213,0.000471303,0.004454036,0.0008743396,0.0001743396,0.0007682567,0.003482674,0.03052068,0.05489633,0.1931082,0.01392749,0.6970907],"study_design_scores_gemma":[0.0001677196,0.0006211162,0.003949192,0.0003959153,0.0002905089,0.001645992,0.0006429813,0.456472,0.1884122,0.1492057,0.1979463,0.000250347],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005992975,0.0001147431,0.984445,0.0002783323,0.00002063501,0.0001591711,0.00003097096,0.005616392,0.003341741],"genre_scores_gemma":[0.1109486,0.0002230865,0.8827861,0.0002958543,0.00003102406,0.0001938636,0.0002357126,0.001433855,0.003851863],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004655819,"threshold_uncertainty_score":0.02379322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009628883067314346,"score_gpt":0.2870251257927625,"score_spread":0.2773962427254481,"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."}}