{"id":"W2502099092","doi":"10.1680/jgrim.14.00016","title":"Optimising deep mixed soil zones in land reclamation projects","year":2016,"lang":"en","type":"article","venue":"Proceedings of the Institution of Civil Engineers - Ground Improvement","topic":"Geotechnical Engineering and Soil Stabilization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of New Brunswick","funders":"","keywords":"Land reclamation; Environmental science; Work (physics); Water table; Civil engineering; Hydrology (agriculture); Geotechnical engineering; Geology; Groundwater; Engineering; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000632133,0.0005430078,0.0003120792,0.0005675123,0.000151962,0.0006902582,0.0003393982,0.0002978931,0.0008048663],"category_scores_gemma":[0.001050859,0.0002341943,0.0002584111,0.000250074,0.0002560975,0.0004094171,0.0006755824,0.0002245084,0.0001658508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002704423,"about_ca_system_score_gemma":0.0002576991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000519069,"about_ca_topic_score_gemma":0.001575424,"domain_scores_codex":[0.9996581,0.0001073446,0.00002387853,0.00004021909,0.0001044315,0.00006614157],"domain_scores_gemma":[0.9993581,0.0002279763,0.0002223582,0.00004915614,0.0001036709,0.00003886428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004874863,0.0001308365,0.009428976,0.0002056828,0.00003470017,0.0001731783,0.000207269,0.4938776,0.4374478,0.0007224235,0.00005119279,0.05723288],"study_design_scores_gemma":[0.00009941142,0.005344633,0.02191119,0.00005166652,0.0001253276,0.0002100157,0.0007536338,0.5940705,0.3729396,0.00183259,0.002605487,0.00005595403],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.932363,0.00009377883,0.06603404,0.00001079088,0.000002172301,0.00003783865,0.00002149588,0.00009025126,0.001346594],"genre_scores_gemma":[0.9944886,0.0000205015,0.005269819,0.000001997932,3.544767e-7,0.000008788553,0.000008570013,0.000007020812,0.0001943618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008048663,"threshold_uncertainty_score":0.003343105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00781889429922991,"score_gpt":0.1809486346080474,"score_spread":0.1731297403088175,"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."}}