{"id":"W3167790180","doi":"10.1108/ecam-12-2020-1060","title":"Mixed qualitative–quantitative approach for bidding decisions in construction","year":2021,"lang":"en","type":"article","venue":"Engineering Construction & Architectural Management","topic":"BIM and Construction Integration","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bidding; Computer science; Quantitative analysis (chemistry); Decision support system; Reuse; Qualitative property; Operations research; Management science; Knowledge management; Data mining; Machine learning; Business; Engineering; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01261351,0.001177739,0.0007897689,0.003427058,0.001082746,0.004183509,0.002103625,0.001064587,0.005243441],"category_scores_gemma":[0.02069276,0.0007124063,0.0013173,0.002243635,0.0018604,0.002947345,0.002404676,0.001455782,0.0005927351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003666961,"about_ca_system_score_gemma":0.003806065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004534112,"about_ca_topic_score_gemma":0.007238912,"domain_scores_codex":[0.9850675,0.01076223,0.0005423906,0.0007085673,0.00263315,0.0002862536],"domain_scores_gemma":[0.9831907,0.01207778,0.001309534,0.0006618374,0.002351775,0.0004083255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004198886,0.000614032,0.01173249,0.001324624,0.0004629431,0.001040849,0.006507118,0.3846723,0.006458774,0.3690209,0.002647161,0.2150989],"study_design_scores_gemma":[0.00004714835,0.0002701945,0.002138529,0.0002323992,0.0001105104,0.0002727646,0.002880037,0.8189739,0.001776994,0.1644198,0.008760138,0.0001175675],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02009308,0.000251841,0.9657578,0.00047361,0.00004258236,0.0004197055,0.0001276906,0.00009921574,0.01273449],"genre_scores_gemma":[0.4612977,0.0002441201,0.5349624,0.0001546059,0.00002626259,0.0007227738,0.0001116321,0.00003901216,0.002441457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01261351,"threshold_uncertainty_score":0.06670749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02858960551835073,"score_gpt":0.2619158157200169,"score_spread":0.2333262102016661,"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."}}