{"id":"W2922729326","doi":"","title":"Adapting methodologies from the forestry industry to measure the productivity of underground hard rock mining equipment","year":2018,"lang":"en","type":"dissertation","venue":"Lu Zone Ul (Laurentian University)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Measure (data warehouse); Productivity; Mining industry; Underground mining (soft rock); Engineering; Forestry; Mining engineering; Business; Natural resource economics; Civil engineering; Computer science; Geography; Economics; Waste management; Data mining; Coal mining; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01151821,0.001612336,0.0007147926,0.01450088,0.001299598,0.004768698,0.001832314,0.001042314,0.002543825],"category_scores_gemma":[0.02509397,0.0005215866,0.00129987,0.01435479,0.001479488,0.002996284,0.003084883,0.001286764,0.001018587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005197079,"about_ca_system_score_gemma":0.006472805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01750163,"about_ca_topic_score_gemma":0.02924821,"domain_scores_codex":[0.9835845,0.005174226,0.002214117,0.001957019,0.006467212,0.0006030148],"domain_scores_gemma":[0.9754263,0.007668638,0.005017602,0.00282051,0.008755263,0.0003115707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000951547,0.0006323711,0.1862355,0.002443848,0.0002855858,0.0003939893,0.007467133,0.01811457,0.01084202,0.05257893,0.005348885,0.7155622],"study_design_scores_gemma":[0.00007310963,0.001442999,0.5339459,0.002723393,0.0003398122,0.00108171,0.02721293,0.05592119,0.03656084,0.0695455,0.2707141,0.0004385453],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1080817,0.00233192,0.8210287,0.0006759538,0.0002330043,0.00232728,0.002502318,0.0005695547,0.0622495],"genre_scores_gemma":[0.2395619,0.00290735,0.7423104,0.0003916596,0.00007369551,0.003173151,0.002777456,0.0001646361,0.00863977],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01750163,"threshold_uncertainty_score":0.06091487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05879956216089397,"score_gpt":0.2447867158752952,"score_spread":0.1859871537144012,"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."}}