{"id":"W2624818832","doi":"10.7492/ijaec.2016.005","title":"Investigating and Ranking Labor Factors Productivity in Egyptian Construction Industry","year":2016,"lang":"en","type":"article","venue":"International Journal of Architecture Engineering and Construction","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ranking (information retrieval); Productivity; Business; Industrial organization; Computer science; Economics; Economic growth; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001075688,0.0002522456,0.0001770964,0.003918155,0.0004073284,0.001149998,0.0001797158,0.0001557304,0.001809929],"category_scores_gemma":[0.003381745,0.00008610618,0.0002024365,0.003650074,0.0002847668,0.0003871975,0.0004400241,0.0001403609,0.0002415278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001434867,"about_ca_system_score_gemma":0.001304664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01453166,"about_ca_topic_score_gemma":0.01551442,"domain_scores_codex":[0.9991701,0.0001491944,0.0000790508,0.00005303586,0.0003487076,0.0001998282],"domain_scores_gemma":[0.9983424,0.000560918,0.0004553929,0.0000405275,0.0005002205,0.0001006513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001641196,0.0001077117,0.8738552,0.0003033322,0.00006639651,0.0002951112,0.00405639,0.002895523,0.002358889,0.001221999,0.0006612634,0.1140141],"study_design_scores_gemma":[0.000003537422,0.0001106374,0.9802004,0.00004846645,0.00002101819,0.00007492184,0.01267782,0.002702927,0.001099333,0.0002635421,0.002784899,0.00001259829],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959704,0.0002604764,0.0008065194,0.00007779529,0.000002740552,0.00001732884,0.0001762539,0.000005738095,0.002682877],"genre_scores_gemma":[0.9985983,0.0002033956,0.000568853,0.000005886295,0.000002128184,0.00000892658,0.0001485183,0.000001170908,0.0004627895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01453166,"threshold_uncertainty_score":0.02889419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02041384587286628,"score_gpt":0.2827003189995845,"score_spread":0.2622864731267182,"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."}}