{"id":"W2147123689","doi":"10.1109/cjece.2007.364327","title":"A new algorithm for finding the optimal solution of the least absolute value estimation problem","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Electrical and Computer Engineering","topic":"Numerical Methods and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Least absolute deviations; Algorithm; Value (mathematics); Mathematical optimization; Estimation; Computer science; Mathematics; Statistics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005368476,0.00008838797,0.0001431145,0.0001203443,0.0001240001,0.00008140079,0.0004069418,0.00003841791,5.137153e-7],"category_scores_gemma":[0.00004377768,0.00005455695,0.00009152422,0.0004220907,0.0000180643,0.0001466518,0.00003079887,0.0001990126,1.177063e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000639262,"about_ca_system_score_gemma":0.0002250396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001993667,"about_ca_topic_score_gemma":0.00001555557,"domain_scores_codex":[0.9991794,0.00002038979,0.0002794823,0.00009727091,0.0001295092,0.0002939198],"domain_scores_gemma":[0.9992136,0.0002369632,0.0001265773,0.00009553845,0.000075708,0.0002515607],"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":[0.000001455643,0.000003865164,0.0000150192,0.000006138702,0.00001920856,0.000004098806,0.0001326029,0.02265682,0.0001128809,0.008700019,0.0001704144,0.9681775],"study_design_scores_gemma":[0.0002079851,0.0001547128,0.002455809,0.00004351937,0.00001040724,0.0001618713,0.000001416135,0.9938766,0.0004342361,0.001216849,0.001364757,0.00007177703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001269577,0.000376661,0.9971589,0.0006934187,0.0003853236,0.0001025307,7.138862e-7,0.000006484285,0.000006317689],"genre_scores_gemma":[0.04936153,0.000002989292,0.9502518,0.00006822355,0.0002949371,8.73283e-7,1.065851e-7,0.000005835272,0.00001369409],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9712198,"threshold_uncertainty_score":0.2224768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009453302953869485,"score_gpt":0.2212061299891923,"score_spread":0.2117528270353229,"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."}}