{"id":"W1485132974","doi":"","title":"Selection of Automated Data Collection Technologies Using Multi Criteria Decision Making Approach for Pavement Management Systems","year":2012,"lang":"en","type":"article","venue":"USC Research Bank (University of the Sunshine Coast)","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data collection; Computer science; Automation; Data quality; Process (computing); Data management; Reliability (semiconductor); Asset (computer security); Data science; Risk analysis (engineering); Data mining; Engineering; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001060768,0.0001066888,0.0002022955,0.0003281004,0.0003401375,0.00002309066,0.0006432797,0.0000908552,0.00000743854],"category_scores_gemma":[0.00007246591,0.00009270251,0.00006461786,0.0006562372,0.0000837876,0.000330836,0.0006921943,0.0001792506,2.80204e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002695951,"about_ca_system_score_gemma":0.00001683006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002787727,"about_ca_topic_score_gemma":0.00005060435,"domain_scores_codex":[0.9989212,0.00007320772,0.0001438918,0.0001715711,0.0003342836,0.0003558365],"domain_scores_gemma":[0.9991667,0.0000799208,0.00007088397,0.000459858,0.000199517,0.00002315999],"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":[0.001354863,0.0008120184,0.0316196,0.0130214,0.006267165,0.00001066935,0.006898702,0.5302023,0.2532935,0.00302382,0.08016415,0.07333183],"study_design_scores_gemma":[0.0004709222,0.00003175504,0.004589117,0.0001921579,0.0001324985,0.000004628437,0.005175964,0.9853799,0.0030462,0.00004568514,0.0008277753,0.0001033836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3667165,0.0003738936,0.6301162,0.00002216314,0.0007099372,0.001359035,0.00007557242,0.0004196264,0.0002070438],"genre_scores_gemma":[0.9125258,0.00004994863,0.0872876,4.179118e-7,0.00003313125,0.000003098045,0.00001264659,0.00001462407,0.00007273418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5458093,"threshold_uncertainty_score":0.3780299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1002216559798486,"score_gpt":0.3403677692132291,"score_spread":0.2401461132333805,"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."}}