{"id":"W2130036064","doi":"10.1061/(asce)0887-3801(2000)14:1(9)","title":"Artificial Neural Network for Measuring Organizational Effectiveness","year":2000,"lang":"en","type":"article","venue":"Journal of Computing in Civil Engineering","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial neural network; Operationalization; Flexibility (engineering); Computer science; Artificial intelligence; Context (archaeology); Set (abstract data type); Machine learning; Data mining; Operations research; Industrial engineering; Engineering; Mathematics; Statistics","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":[0.001825793,0.0007406923,0.0006020445,0.001685124,0.0002606912,0.0008622516,0.0006921689,0.0009511667,0.001758238],"category_scores_gemma":[0.007664667,0.0001674918,0.0003743787,0.00253837,0.0002595687,0.001006797,0.0004682031,0.0008785232,0.0003940071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008629243,"about_ca_system_score_gemma":0.0006020642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003327882,"about_ca_topic_score_gemma":0.002575745,"domain_scores_codex":[0.9987645,0.0004390269,0.000124015,0.0001458621,0.000453726,0.00007276095],"domain_scores_gemma":[0.998215,0.0009863938,0.0002475351,0.00008825923,0.0004197446,0.00004323946],"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":[0.0005525086,0.0007074326,0.05884775,0.0006728285,0.000439287,0.0002411649,0.0003208625,0.4284508,0.007421969,0.02035724,0.006534816,0.4754534],"study_design_scores_gemma":[0.00002616986,0.0003057745,0.02244777,0.000101991,0.00005847759,0.00007676199,0.0001292144,0.9633624,0.003366363,0.006542534,0.003539286,0.00004330403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2402105,0.002023861,0.7349754,0.0006148634,0.0002977492,0.0007610781,0.003264026,0.001120509,0.01673204],"genre_scores_gemma":[0.7899315,0.000924225,0.2022703,0.0001382055,0.00005258335,0.001308399,0.001586862,0.00002727593,0.003760744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003327882,"threshold_uncertainty_score":0.009655833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01324290052618696,"score_gpt":0.2233417308620171,"score_spread":0.2100988303358301,"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."}}