{"id":"W2732266022","doi":"10.1061/9780784480793.037","title":"A Retrospective Evaluation of the Progress of Computer Monitored Grouting","year":2017,"lang":"en","type":"article","venue":"Grouting 2017","topic":"Grouting, Rheology, and Soil Mechanics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Golder Associates (Canada)","funders":"","keywords":"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":[0.001446877,0.0001529191,0.0002847632,0.00004370478,0.0003648273,0.00004409115,0.0006074248,0.0001296462,0.000003896447],"category_scores_gemma":[0.0004001812,0.000124352,0.0001196191,0.0000555474,0.0002075474,0.0001213772,0.0002007452,0.000207964,0.000003292702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009136694,"about_ca_system_score_gemma":0.00003227284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006286639,"about_ca_topic_score_gemma":0.00001559041,"domain_scores_codex":[0.9986687,0.00009429982,0.0003487584,0.0001882347,0.0004325694,0.0002673803],"domain_scores_gemma":[0.9982689,0.00003110793,0.0005100621,0.0008483195,0.0003094359,0.0000321862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002225445,0.00009499111,0.9151655,0.0003316429,0.0003268628,0.000003653874,0.009424653,0.004368069,0.004071769,0.01660133,0.000309164,0.04928007],"study_design_scores_gemma":[0.0005655159,0.00003323426,0.6118096,0.0001932434,0.00008609847,0.000005834835,0.000170349,0.3813295,0.003917435,0.001750709,0.000006732309,0.0001318517],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904552,0.0001395486,0.001282892,0.0000317173,0.001897444,0.000311319,0.000007610202,0.00007653671,0.005797755],"genre_scores_gemma":[0.9987171,0.00000379613,0.0009744109,0.000003563865,0.000245165,0.0000113082,0.000001825948,0.00002468486,0.00001809537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3769614,"threshold_uncertainty_score":0.5070929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03359789549376892,"score_gpt":0.280715277121233,"score_spread":0.2471173816274641,"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."}}