{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008212586,0.0001224738,0.0001821767,0.0009111798,0.00005050967,0.0001367088,0.000175885,0.00008887062,0.00003134496],"category_scores_gemma":[0.001258248,0.00008009196,0.00003941824,0.0003063009,0.000182117,0.0005674701,0.000066336,0.0003671628,5.408854e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004584499,"about_ca_system_score_gemma":0.00004325064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001091437,"about_ca_topic_score_gemma":0.00001141091,"domain_scores_codex":[0.9985647,0.00005685452,0.0005148049,0.0002021085,0.0005427495,0.0001187488],"domain_scores_gemma":[0.9989517,0.0003029143,0.000349794,0.00008546386,0.0002396944,0.00007044277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002663515,0.0000048662,0.493494,0.000005654415,0.00003660714,0.000004095228,0.0005365738,0.0009962982,0.005648912,0.002158349,0.000006444974,0.4970815],"study_design_scores_gemma":[0.002356863,0.0001243322,0.9520087,0.0006445155,0.00002855641,0.003286661,0.002024869,0.00161217,0.005527947,0.0242338,0.007734281,0.0004173156],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987551,0.000065602,0.008528891,0.002029468,0.001678579,0.00005588518,0.000005291252,0.00001605333,0.00006920332],"genre_scores_gemma":[0.9912464,0.00004032948,0.008355765,0.00001734564,0.0003067925,0.000001110161,3.448373e-7,0.00000600423,0.00002588405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4966642,"threshold_uncertainty_score":0.3266055,"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."}}