{"id":"W2987553030","doi":"10.3390/su11216127","title":"Determination of GPS Session Duration in Ground Deformation Surveys in Mining Areas","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"GNSS positioning and interference","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Geodetic datum; Geodesy; Geology; Deformation (meteorology); Subsidence; Displacement (psychology); Rock mass classification; Overburden; Deformation monitoring; Global Positioning System; Groundwater-related subsidence; Geotechnical engineering; Computer science","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":[0.0006566431,0.0002623341,0.0003865905,0.001759296,0.0002174666,0.0003232555,0.00026078,0.0002661468,0.001212669],"category_scores_gemma":[0.002651073,0.0001126681,0.0002012057,0.001772887,0.00009400595,0.0002469149,0.0002608815,0.0001434733,0.0007151244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000246684,"about_ca_system_score_gemma":0.0003048611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004663865,"about_ca_topic_score_gemma":0.007535999,"domain_scores_codex":[0.9992913,0.0001453089,0.00008128813,0.0002016553,0.0001861375,0.00009430776],"domain_scores_gemma":[0.9985645,0.000398711,0.0002982055,0.0001298318,0.0004492736,0.000159515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006337401,0.00008806807,0.8798599,0.0003289933,0.00008184458,0.0003518212,0.001271791,0.003944237,0.01188206,0.0002132033,0.002502577,0.09884179],"study_design_scores_gemma":[0.000008511373,0.0001723524,0.989678,0.00002314988,0.00004278655,0.0002916358,0.0004305542,0.004742514,0.001435038,0.00006529093,0.003098691,0.00001155691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980025,0.0004166446,0.009956829,0.00005155618,0.00004806999,0.0001189434,0.005104951,0.0003674643,0.003910604],"genre_scores_gemma":[0.9898127,0.0002421462,0.004522502,0.00002630743,0.0000365615,0.0001290306,0.004252549,0.00002653521,0.0009515762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004663865,"threshold_uncertainty_score":0.00927341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007193573982381669,"score_gpt":0.2395295517176594,"score_spread":0.2323359777352778,"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."}}