{"id":"W3010568754","doi":"10.1139/cjce-2019-0739","title":"Modelling a cost profile for road projects","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Johannesburg","keywords":"Transport engineering; Scope (computer science); Work (physics); Upgrade; Cost estimate; Road construction; Cost overrun; Data collection; Cost analysis; Cost database; Estimation; Engineering; Computer science; Construction engineering; Operations research; Systems engineering; Construction industry; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007095481,0.0000898501,0.0001859369,0.0004297502,0.00008360075,0.0001986259,0.0003712664,0.00003334026,0.0001886112],"category_scores_gemma":[0.0009466902,0.00007776039,0.0001053883,0.0005513756,0.00001609753,0.0003990189,0.00001164485,0.0001455104,0.00001827303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004548173,"about_ca_system_score_gemma":0.0004934595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001238022,"about_ca_topic_score_gemma":0.003837108,"domain_scores_codex":[0.9988855,0.00001021736,0.0004355177,0.0001266891,0.000298027,0.0002440269],"domain_scores_gemma":[0.9988797,0.0001146141,0.0001725632,0.000100149,0.0002997642,0.0004331975],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001142128,0.000001832162,0.001004628,0.00003628992,0.00002868151,0.00002008163,0.001511893,0.954939,0.0000778909,0.0008188075,0.02198111,0.01956836],"study_design_scores_gemma":[0.0002281039,0.00005017814,0.00007183955,0.00003048174,0.000008037461,0.000018867,0.0002500574,0.7519298,0.0001086004,0.0001225278,0.2471178,0.00006369151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06074924,0.0005672785,0.9245401,0.001626204,0.001577754,0.0006091442,0.00002958752,0.00002765259,0.010273],"genre_scores_gemma":[0.9961283,0.000007019059,0.003091208,0.0001347043,0.0003611178,0.000007756182,7.84612e-7,0.00001192985,0.0002571927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.935379,"threshold_uncertainty_score":0.3170977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1057432088552745,"score_gpt":0.2851926666412547,"score_spread":0.1794494577859802,"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."}}