{"id":"W4245993114","doi":"10.22215/etd/2005-08092","title":"A robust fit for generalized additive models","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Humanities; Mathematics; Computer science; Art","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":[0.0001878697,0.0003379718,0.000615061,0.0000750322,0.00009758185,0.00002788079,0.0001523917,0.0003291835,0.0006767467],"category_scores_gemma":[0.0006732594,0.000286629,0.000222556,0.00005546252,0.00001655856,0.0001154133,0.0000124382,0.0001923025,0.000008765342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006158355,"about_ca_system_score_gemma":0.00007737298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007837076,"about_ca_topic_score_gemma":0.0002781753,"domain_scores_codex":[0.9984925,0.00004785774,0.0004586444,0.0004505072,0.000214484,0.0003359538],"domain_scores_gemma":[0.9978007,0.001296695,0.0002230758,0.0002670907,0.0003016501,0.0001107606],"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":[0.000161145,0.00007287097,6.004016e-9,0.0002401512,0.00006791907,0.000001419854,0.0002800389,0.001162076,0.00003102711,0.939892,0.01621842,0.04187293],"study_design_scores_gemma":[0.0005912247,0.00005051319,3.363133e-7,0.0000870542,0.0002124945,8.526673e-7,0.0002435621,0.09067682,0.0005082244,0.90358,0.003686207,0.0003627511],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001556907,0.00009517928,0.9334604,0.0000335994,0.0002405576,0.0009991814,0.0008822553,0.0001141454,0.06401896],"genre_scores_gemma":[0.0001486943,0.00009008113,0.8503225,0.0001097504,0.0002883042,0.0006498774,0.001053498,0.00009928524,0.147238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08951475,"threshold_uncertainty_score":0.9999586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2909380796516575,"score_gpt":0.4627228506601762,"score_spread":0.1717847710085186,"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."}}