{"id":"W2437294271","doi":"","title":"Understanding variation in revenue and expenses.","year":2002,"lang":"en","type":"article","venue":"PubMed","topic":"Quality and Supply Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Revenue; Variation (astronomy); Identification (biology); Control (management); Control chart; Process (computing); Business; Operations management; Computer science; Operations research; Finance; Economics; Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004941566,0.0004239714,0.0005072636,0.004716108,0.0003470423,0.002260347,0.0005722269,0.0005597731,0.002968967],"category_scores_gemma":[0.04390469,0.0001677548,0.0004185395,0.005653016,0.0004928478,0.003492268,0.0007443003,0.0008174731,0.000545457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001530432,"about_ca_system_score_gemma":0.001358167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02043923,"about_ca_topic_score_gemma":0.01299237,"domain_scores_codex":[0.9953877,0.001452939,0.0004511201,0.0006324745,0.001901489,0.0001741711],"domain_scores_gemma":[0.9760422,0.01425486,0.004529294,0.001203788,0.003688933,0.0002809584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003153515,0.0002024358,0.2640373,0.0005671173,0.0003792741,0.0004136139,0.002822815,0.03212992,0.0009759035,0.08621221,0.03809945,0.5738446],"study_design_scores_gemma":[0.00004225454,0.0002613511,0.5903769,0.0005883576,0.0001940134,0.0008508811,0.002624192,0.1012371,0.001742134,0.1742198,0.1276359,0.0002270961],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5694881,0.02279973,0.2493045,0.01527093,0.001193652,0.000474436,0.03254054,0.001672867,0.1072552],"genre_scores_gemma":[0.9536088,0.003762889,0.02985679,0.0004040044,0.0002629921,0.0001414279,0.008856524,0.0001006185,0.003005998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02043923,"threshold_uncertainty_score":0.04064053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1536419106766354,"score_gpt":0.2148414046237764,"score_spread":0.06119949394714094,"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."}}