{"id":"W3003591222","doi":"10.3311/ccc2019-027","title":"Toward a Qualitative RFIs Content Analysis Approach to Improve Collaboration Between Design and Construction Phases","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Creative Construction Conference 2019","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Content (measure theory); Content analysis; Data science; Management science; Engineering; Mathematics; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00231356,0.0003057068,0.0007639767,0.0009836793,0.0002505334,0.0005202295,0.0006032372,0.0001258953,0.000316301],"category_scores_gemma":[0.001260758,0.0002141559,0.0001866986,0.003706541,0.0007335941,0.001292307,0.0002672892,0.000206449,0.00003400945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009055724,"about_ca_system_score_gemma":0.000165664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009736428,"about_ca_topic_score_gemma":0.000002960757,"domain_scores_codex":[0.9966546,0.0001751433,0.0009834763,0.0008527748,0.001060075,0.0002739108],"domain_scores_gemma":[0.99431,0.0005615244,0.001248521,0.0002865169,0.00346035,0.000133068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0009548053,0.000111781,0.5734438,0.0001442971,0.002059651,9.326259e-8,0.04237122,0.0002450179,0.02288214,0.2472643,0.001989191,0.1085338],"study_design_scores_gemma":[0.004993301,0.001366713,0.128881,0.0002754115,0.002686318,0.00004699437,0.6494699,0.02265643,0.1171002,0.06720524,0.003472592,0.001845837],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.900089,0.00002695123,0.08190984,0.0009024954,0.0004858086,0.001870952,0.0001211233,0.0000482376,0.01454559],"genre_scores_gemma":[0.960339,0.00002830757,0.03680316,0.0000506083,0.00005670227,0.00007160985,0.000007858172,0.00001027225,0.002632468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6070987,"threshold_uncertainty_score":0.8733023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1960581811872806,"score_gpt":0.3792943478014002,"score_spread":0.1832361666141196,"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."}}