{"id":"W2891421616","doi":"10.1051/matecconf/201819604089","title":"Use of Pairwise Comparison Method in Road-and-Bridge Tenders","year":2018,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Call for bids; Pairwise comparison; Bridge (graph theory); Diversification (marketing strategy); Point (geometry); Computer science; Function (biology); Operations research; Presentation (obstetrics); Quality (philosophy); Procurement; Transport engineering; Business; Marketing; Engineering; Mathematics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.08394565,0.001563663,0.002647336,0.008416956,0.002196942,0.004018541,0.00384434,0.001831279,0.01356237],"category_scores_gemma":[0.2211104,0.0007110673,0.002178404,0.01027267,0.003281203,0.004571242,0.004436546,0.003290531,0.001678616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002422433,"about_ca_system_score_gemma":0.002936938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001209227,"about_ca_topic_score_gemma":0.001479577,"domain_scores_codex":[0.7836406,0.1858741,0.004479597,0.006505849,0.01785727,0.001642525],"domain_scores_gemma":[0.784516,0.1869771,0.006285015,0.006589422,0.01407804,0.001554485],"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":[0.001818578,0.0005660016,0.007010365,0.003244286,0.001154542,0.0008291977,0.007392533,0.05454063,0.004684353,0.2314608,0.00881041,0.6784883],"study_design_scores_gemma":[0.0005024144,0.003430043,0.01344364,0.00103469,0.0006547594,0.001516954,0.006163697,0.3567998,0.01152138,0.5346344,0.06978104,0.0005171848],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0155332,0.0005201558,0.9748361,0.0002136642,0.0002278244,0.001053144,0.0002502427,0.0002108521,0.007154786],"genre_scores_gemma":[0.1817163,0.0003614589,0.813387,0.00008493466,0.0001786948,0.00198886,0.0003814431,0.0002340577,0.001667232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08394565,"threshold_uncertainty_score":0.4439523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2893054254026324,"score_gpt":0.429376696257783,"score_spread":0.1400712708551506,"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."}}