{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027862,0.00006771756,0.0001093767,0.0001509416,0.00001202825,0.00001404522,0.00005111993,0.0000653576,0.00001362667],"category_scores_gemma":[0.0002274767,0.0000707017,0.00001793397,0.0002177411,0.0000142781,0.0004571357,0.00001315858,0.00008839612,0.000002901664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006428686,"about_ca_system_score_gemma":0.00003934263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002182867,"about_ca_topic_score_gemma":0.0002781525,"domain_scores_codex":[0.9992014,0.0001787595,0.0003055063,0.000100151,0.0000887545,0.0001254677],"domain_scores_gemma":[0.999592,0.00006668936,0.00004355512,0.0001311035,0.0001522677,0.00001436589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001773847,0.00008069947,0.9338239,0.0009090637,0.000001785284,0.000001121816,0.005038004,0.02087756,0.001914811,0.000447311,0.000005622514,0.0368824],"study_design_scores_gemma":[0.0002039149,0.00003408694,0.8451769,0.00007937603,9.465863e-7,8.936901e-7,0.001121166,0.1494456,0.002123592,0.00174282,0.000002827297,0.00006778324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903854,0.00001181159,0.008237056,0.00002357527,0.00009239792,0.000218361,0.000001224732,0.00003426016,0.0009959114],"genre_scores_gemma":[0.9997532,0.000001729572,0.0001660748,0.000001666399,0.000005047409,0.00001495337,0.0000228808,0.000005547263,0.00002887794],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1285681,"threshold_uncertainty_score":0.2883132,"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."}}