{"id":"W2124988298","doi":"10.1002/wics.165","title":"Computations using analysis of covariance","year":2011,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; University of New Brunswick","funders":"","keywords":"Analysis of covariance; Covariate; Statistics; Nonparametric statistics; Regression analysis; Mathematics; Analysis of variance; Linear regression; Econometrics; Covariance; Statistical hypothesis testing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009870772,0.0008143503,0.005896902,0.0008249441,0.0002501233,0.00003657658,0.0006144593,0.000261222,0.0004095736],"category_scores_gemma":[0.0008325352,0.0006835426,0.001282623,0.001916581,0.0003359491,0.000123063,0.0006420694,0.0005195458,0.00003825901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000229239,"about_ca_system_score_gemma":0.0003065137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008190867,"about_ca_topic_score_gemma":0.00001127859,"domain_scores_codex":[0.9937243,0.001062295,0.003554794,0.0008146463,0.0004230473,0.0004209013],"domain_scores_gemma":[0.9897634,0.005859761,0.003005176,0.0006625921,0.000494444,0.0002145821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008100547,0.000214059,6.560261e-7,0.01475274,0.002006126,0.0000158058,0.0002226351,0.004375688,2.950664e-8,0.3390554,0.001403989,0.6379448],"study_design_scores_gemma":[0.0001419537,0.0001115269,0.000002538927,0.01549547,0.02419038,0.0000417378,0.00001896799,0.1210917,2.195018e-8,0.6523072,0.1858377,0.0007608281],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[1.206712e-7,0.4763029,0.5181958,0.000001362818,0.000163239,0.0007089218,0.00448327,0.0000250805,0.0001192904],"genre_scores_gemma":[5.846256e-7,0.4874575,0.5112702,0.000009038024,0.00004486429,0.00006427617,0.001050885,0.0000571686,0.00004545957],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.637184,"threshold_uncertainty_score":0.9995615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3841182895742637,"score_gpt":0.5345027831583571,"score_spread":0.1503844935840934,"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."}}