{"id":"W1936446011","doi":"10.1139/cjce-2014-0031","title":"Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Natural Resources","funders":"","keywords":"Productivity; Context (archaeology); Identification (biology); Key (lock); Business; Engineering; Computer science; Economics; Economic growth; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002205489,0.00007744005,0.0003071217,0.002433951,0.00005115705,0.0001439993,0.0001143036,0.00004025091,0.0000125824],"category_scores_gemma":[0.001215615,0.00007194351,0.00003724878,0.001690603,0.00008230352,0.0006181551,0.00001377086,0.0001624331,1.575017e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005522366,"about_ca_system_score_gemma":0.0001301777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008938847,"about_ca_topic_score_gemma":0.0380596,"domain_scores_codex":[0.9988714,0.0000701337,0.0005476353,0.0001487854,0.000236839,0.0001252045],"domain_scores_gemma":[0.9989846,0.0002089547,0.0003894421,0.0001098856,0.0001908963,0.0001162209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001871336,0.000003791686,0.8542989,0.00002467938,0.0001717169,0.000002399273,0.003321966,0.1114384,0.002802763,0.004922504,0.00002597062,0.02296813],"study_design_scores_gemma":[0.0006388922,0.00006994989,0.8736112,0.0001258357,0.0001744345,0.00004679435,0.001795796,0.1192649,0.001733603,0.0006838003,0.001651915,0.000202852],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937938,0.00006707397,0.005580267,0.00007950135,0.0002906413,0.0000832195,0.000003064921,0.000002559094,0.0000998863],"genre_scores_gemma":[0.9992031,0.000005753521,0.0007367156,0.000004139425,0.00003779483,0.000001102326,2.574303e-7,0.000002056531,0.000009009818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03716572,"threshold_uncertainty_score":0.9794933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06481635670394066,"score_gpt":0.2867549828379044,"score_spread":0.2219386261339638,"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."}}