{"id":"W2786387705","doi":"10.1139/cjce-2017-0359","title":"Location-based planning and scheduling of highway construction projects in hilly terrain using GIS","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terrain; Plan (archaeology); Geographic information system; Transport engineering; Computer science; Scheduling (production processes); Variety (cybernetics); Engineering; Geography; Remote sensing; Cartography; Operations management","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":[0.0001569755,0.00009644992,0.0001514442,0.0006758799,0.00003456392,0.00002697585,0.00005575149,0.00007249581,0.00002035204],"category_scores_gemma":[0.00007285572,0.0001065914,0.00002376107,0.0003154568,0.00006583247,0.0001856879,0.000001852711,0.0001687969,2.47675e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001233953,"about_ca_system_score_gemma":0.0003373885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000429781,"about_ca_topic_score_gemma":0.01271835,"domain_scores_codex":[0.9993682,0.000009209968,0.0003253399,0.00006245723,0.00007753065,0.000157285],"domain_scores_gemma":[0.999555,0.00002411169,0.00007803463,0.00005882121,0.0001501314,0.0001339358],"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":[0.00000492075,0.000001643081,0.0163003,0.0001456179,0.00002626464,0.00001138921,0.000965005,0.9664369,0.01330446,0.0006364211,0.00001486202,0.002152238],"study_design_scores_gemma":[0.0004709318,0.00005647545,0.007339185,0.001336546,0.00001878871,0.0002525671,0.0005227348,0.9789971,0.0104252,0.00006284264,0.0003266665,0.000191005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8190388,0.0009210096,0.1788023,0.00002401376,0.0008084544,0.00005610971,0.000002585911,0.00001996476,0.000326761],"genre_scores_gemma":[0.9921361,0.000002316541,0.007679666,0.000006711709,0.0001562565,9.302094e-7,7.225653e-7,0.00001649078,8.331177e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1730973,"threshold_uncertainty_score":0.7097135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01118526872841732,"score_gpt":0.2001879219254669,"score_spread":0.1890026531970496,"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."}}