{"id":"W7095174563","doi":"","title":"Copyright © Canadian Academy of Oriental and Occidental Culture Efficiency Measurement in Turkish Coal Enterprises Using Data Envelopment","year":2013,"lang":"en","type":"article","venue":"","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Data envelopment analysis; Turkish; Coal; Government (linguistics); Coal mining","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00319602,0.000232039,0.0004251869,0.0007538141,0.0002177787,0.0003074076,0.001612073,0.0001349716,0.001065264],"category_scores_gemma":[0.0007992717,0.000162055,0.00006268883,0.001140893,0.000284521,0.0008409065,0.0005446004,0.0002217161,0.0001000693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000374293,"about_ca_system_score_gemma":0.0003863682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07241391,"about_ca_topic_score_gemma":0.05253155,"domain_scores_codex":[0.9948725,0.0001958092,0.001067695,0.0009077775,0.002449077,0.000507109],"domain_scores_gemma":[0.9984381,0.0001462939,0.0002639786,0.0005726889,0.000224923,0.0003540392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003693893,0.0006465811,0.9029061,0.00002218884,0.0001214384,0.00004369789,0.006802782,0.001473447,0.03099088,0.0004685065,0.04758358,0.008903868],"study_design_scores_gemma":[0.002762351,0.0002080648,0.6506218,0.0003872702,0.0001820908,0.0001975942,0.01905757,0.2656607,0.02063567,0.002398041,0.03604938,0.001839444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938633,0.0004923464,0.00176924,0.0005723788,0.0002120299,0.000411899,0.000046087,0.00001567281,0.002616992],"genre_scores_gemma":[0.996985,0.00001817549,0.002317145,0.0004069263,0.00002811895,0.000004058879,0.00001059276,0.000008784211,0.000221267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2641872,"threshold_uncertainty_score":0.9998479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.160181709890555,"score_gpt":0.3781946063589081,"score_spread":0.2180128964683531,"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."}}