{"id":"W2355125476","doi":"","title":"Pavement Preventive Maintenance Decision-Making Based on Group Analytical Hierarchy Process","year":2015,"lang":"en","type":"article","venue":"Technology and Economy in Areas of Communications","topic":"Evaluation and Optimization Models","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Preventive maintenance; Analytic hierarchy process; Group decision-making; Reliability (semiconductor); Engineering; Process (computing); Measure (data warehouse); Operations research; Selection (genetic algorithm); Risk analysis (engineering); Transport engineering; Computer science; Reliability engineering; Data mining; Artificial intelligence; Business; Psychology","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":[0.0002722996,0.00006982018,0.000129127,0.0004150482,0.00003908781,0.000007524169,0.0003119581,0.00008168948,0.00002096019],"category_scores_gemma":[0.00011581,0.00007347581,0.00001605534,0.0003060738,0.0001541571,0.00008854356,0.00006305015,0.0001513356,0.000005017365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005667831,"about_ca_system_score_gemma":0.00002976309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.412274e-7,"about_ca_topic_score_gemma":0.00002285103,"domain_scores_codex":[0.9994954,0.00002385267,0.0002472153,0.00009470846,0.00004350166,0.00009532063],"domain_scores_gemma":[0.9991634,0.0001571635,0.00004527291,0.0005273339,0.00007674494,0.00003010153],"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":[0.00002774046,0.0002271521,0.0305305,0.00002725645,0.0000320725,6.570378e-7,0.0003833216,0.6730734,0.000001421513,0.2727511,0.0002537644,0.02269167],"study_design_scores_gemma":[0.000403208,0.00003052846,0.0009841737,0.0001216145,0.000005767536,8.596613e-7,0.0002845101,0.9021816,0.00002193684,0.09505073,0.0008441776,0.00007088853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.222962,0.001185935,0.6709939,0.008204835,0.00007995604,0.001016885,0.00001998886,0.0005189003,0.09501757],"genre_scores_gemma":[0.9829199,0.00006652695,0.01679759,0.0001030258,0.000001627301,0.00008563374,0.000009276361,0.000007025482,0.000009346825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.759958,"threshold_uncertainty_score":0.2996257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02977015127112938,"score_gpt":0.3110782128542525,"score_spread":0.2813080615831232,"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."}}