{"id":"W2885648445","doi":"10.1155/2018/9267306","title":"Engaging Multiple Actors in Large-Scale Transport Infrastructure Project Appraisal: An Application of MAMCA to the Case of HS2 High-Speed Rail","year":2018,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Strategic Research Council; Innovationsfonden","keywords":"Project appraisal; Process (computing); Usability; Weighting; Scale (ratio); Government (linguistics); Sustainability; Computer science; Process management; Management science; Data collection; Operations research; Risk analysis (engineering); Engineering; Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06497096,0.001171594,0.0007810891,0.004516858,0.009530742,0.006317611,0.002989821,0.004372285,0.005326695],"category_scores_gemma":[0.05434034,0.0009032919,0.001190088,0.004832369,0.005723489,0.006907151,0.0106046,0.003777539,0.0006792969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009007561,"about_ca_system_score_gemma":0.008719521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007968506,"about_ca_topic_score_gemma":0.01622066,"domain_scores_codex":[0.8965493,0.0938141,0.001708451,0.001900752,0.003238436,0.002788992],"domain_scores_gemma":[0.9106409,0.07733558,0.002466874,0.002667208,0.005132457,0.001757034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0006342272,0.0009870102,0.009964325,0.002191687,0.0001282504,0.01595939,0.7027226,0.00956193,0.008772617,0.07317312,0.005069484,0.1708354],"study_design_scores_gemma":[0.0002911157,0.001231243,0.01049054,0.002028882,0.0001236873,0.003161113,0.7861743,0.05253156,0.005045252,0.04657311,0.09206644,0.0002826862],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6753032,0.00128002,0.2129628,0.01444819,0.0003937819,0.006482372,0.0002271159,0.0002657807,0.08863662],"genre_scores_gemma":[0.7594525,0.0008365771,0.2298296,0.0006821071,0.00007968174,0.003180632,0.00008357083,0.0000459034,0.005809475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06497096,"threshold_uncertainty_score":0.3436034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007419992089531657,"score_gpt":0.2953238234038707,"score_spread":0.2879038313143391,"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."}}