{"id":"W2017902463","doi":"10.1139/t10-009","title":"Quantitative prop support estimation and remote monitor early warning for hard roof weighting at the Muchengjian Mine in China","year":2010,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Geoscience and Mining Technology","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tai'shan Scholar Engineering Construction Fund of Shandong Province of China","keywords":"Roof; Coal mining; Bedding; Geotechnical engineering; Excavation; Mining engineering; Weighting; Warning system; Span (engineering); Bed; Geology; Coal; Engineering; Environmental science; Civil engineering; Waste 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":[0.000627582,0.0001176223,0.0001423832,0.0002542828,0.0002952197,0.00007045004,0.000234856,0.0001924956,0.00002336626],"category_scores_gemma":[0.0005896185,0.00009356633,0.00003698335,0.000192571,0.0001382513,0.0001414645,0.00002884053,0.0008949201,0.000007279011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376025,"about_ca_system_score_gemma":0.0001154462,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003092268,"about_ca_topic_score_gemma":0.02705333,"domain_scores_codex":[0.9990461,0.00001455062,0.000245778,0.0001498813,0.00009736504,0.0004463168],"domain_scores_gemma":[0.9994405,0.00007068703,0.00005637393,0.0001507836,0.00004455608,0.0002371221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006813566,0.00002708307,0.01090027,0.0001057929,0.00007438818,0.0003665406,0.004124013,0.03540728,0.09355335,0.002621149,0.005521815,0.8472302],"study_design_scores_gemma":[0.0006197373,0.0003523372,0.07984658,0.0001096937,0.00002535649,0.0009350932,0.0002186489,0.9017408,0.002229686,0.003432822,0.01013325,0.0003559251],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860007,0.00006729268,0.01061703,0.002671901,0.0002922933,0.0002044911,0.000008693335,0.00006764203,0.00007002494],"genre_scores_gemma":[0.977063,0.00001286625,0.02268367,0.00003984428,0.00006909322,0.000009375438,0.000003386471,0.00001941206,0.00009937463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8663336,"threshold_uncertainty_score":0.9907004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01156442285141024,"score_gpt":0.2377206005775162,"score_spread":0.226156177726106,"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."}}