{"id":"W2400666807","doi":"10.1061/9780784479827.009","title":"Framework for Assessing the Impact of Construction Research and Development on the Construction Industry and Academia","year":2016,"lang":"en","type":"article","venue":"Construction Research Congress 2016","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Construction industry; Incentive; Plan (archaeology); Computer science; Construction management; Process management; Engineering management; Engineering; Construction engineering; Economics; Civil engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03940897,0.00338282,0.001389537,0.01509972,0.003400592,0.01173125,0.004046409,0.003797357,0.007123057],"category_scores_gemma":[0.02427318,0.001004808,0.003439411,0.005756165,0.009676931,0.008191609,0.0055776,0.003454889,0.001263123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02232128,"about_ca_system_score_gemma":0.02851283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02470911,"about_ca_topic_score_gemma":0.02146709,"domain_scores_codex":[0.9570136,0.02571283,0.002790039,0.002152164,0.01050766,0.001823629],"domain_scores_gemma":[0.9773094,0.01172113,0.002180715,0.001320557,0.006505529,0.0009627701],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004147889,0.0001620829,0.001909927,0.0004053958,0.00007485714,0.0001778373,0.0004674214,0.02919113,0.0005198088,0.9406443,0.002871437,0.02353432],"study_design_scores_gemma":[0.0001370152,0.0003817223,0.00292219,0.001635983,0.0001958066,0.0003123864,0.002135949,0.0922688,0.00199591,0.8468679,0.05095729,0.000189119],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008799587,0.001265323,0.8579744,0.01058561,0.0001661985,0.003512133,0.00134018,0.0004529166,0.1159038],"genre_scores_gemma":[0.1775124,0.001210783,0.8098757,0.0009904513,0.0000856528,0.005062224,0.0007970705,0.0000596223,0.004406042],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.960591,"threshold_uncertainty_score":0.2084171,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4111029639963691,"score_gpt":0.555760464238893,"score_spread":0.1446575002425239,"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."}}