{"id":"W2522903462","doi":"10.1007/978-3-319-39065-9_6","title":"Applications of Robust Regression to “Big” Data Problems","year":2016,"lang":"en","type":"book-chapter","venue":"Springer proceedings in mathematics & statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Confidence interval; Robust regression; Econometrics; Regression; Statistics; Regression analysis; Computer science; Quarter (Canadian coin); Robustness (evolution); Geography; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001352781,0.0007387653,0.001439569,0.0004498637,0.00009635411,0.00005749623,0.001402564,0.000440642,0.0001168847],"category_scores_gemma":[0.002688833,0.0005926208,0.00008190316,0.0001251746,0.0002469112,0.0001400313,0.001196333,0.0006329341,0.00006210282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001783778,"about_ca_system_score_gemma":0.0001366475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003225949,"about_ca_topic_score_gemma":0.00002497158,"domain_scores_codex":[0.995477,0.00001204518,0.001914619,0.001081133,0.0009339436,0.0005813263],"domain_scores_gemma":[0.9944631,0.001744532,0.001406737,0.001362727,0.0007471549,0.000275721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001392506,0.0001385356,0.000003384351,0.004398471,0.00005632094,0.000006821854,0.0005391614,0.000003677133,0.000135906,0.8977939,0.003072651,0.09383724],"study_design_scores_gemma":[0.0002946025,0.00007905441,0.000001289582,0.004300943,0.000184548,0.000008064328,0.00005252614,0.0007729239,0.00007707516,0.9263121,0.06728502,0.0006317784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000002229211,0.000114892,0.8368604,0.00006444191,0.0001421589,0.001914349,0.002835216,0.00008549304,0.1579809],"genre_scores_gemma":[0.00003904075,0.0003456707,0.9013833,0.00002372512,0.0003243523,0.0002007031,0.00005047451,0.0002653086,0.09736741],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09320546,"threshold_uncertainty_score":0.9996525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1991257907698016,"score_gpt":0.3944264162600678,"score_spread":0.1953006254902662,"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."}}