{"id":"W4399578393","doi":"10.32614/cran.package.crs","title":"crs: Categorical Regression Splines","year":2011,"lang":"en","type":"dataset","venue":"","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Categorical variable; Regression; Multivariate adaptive regression splines; Statistics; Mathematics; Computer science; Artificial intelligence; Nonparametric regression","routes":{"ca_aff":false,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002277084,0.0003173891,0.0005564244,0.00006742032,0.00006031364,0.00001577486,0.0002975792,0.0003777568,0.002276415],"category_scores_gemma":[0.001497483,0.0001950915,0.00009727796,0.00006740652,0.0000618786,0.00004494358,0.0001761802,0.0004202198,0.0002251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002584381,"about_ca_system_score_gemma":0.00003715878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001055454,"about_ca_topic_score_gemma":0.00004107375,"domain_scores_codex":[0.9985833,0.00009661986,0.0004052718,0.0003956787,0.0002387091,0.0002804072],"domain_scores_gemma":[0.9979793,0.0009095773,0.0001804042,0.0006934917,0.00008378919,0.000153382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001488739,0.00009886568,4.1959e-8,0.0001490849,0.00001384533,0.00004036172,0.000005439039,4.196202e-8,0.000001240814,0.09354276,0.9026124,0.003521028],"study_design_scores_gemma":[0.00006404887,0.00002953165,1.281734e-7,0.00003819384,0.00005110702,0.000006929684,0.000004004879,0.00001389084,0.00002096543,0.5067242,0.4928897,0.0001572559],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[9.68388e-8,0.00004146377,0.4459443,0.00002042881,0.000207182,0.0001096086,0.5527547,0.00004150426,0.0008807039],"genre_scores_gemma":[3.972553e-7,0.0001548596,0.4773157,0.00006036154,0.0002153259,0.00002368034,0.5203421,0.00002264084,0.001864978],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4131815,"threshold_uncertainty_score":0.9986356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2773712994377125,"score_gpt":0.4878550673423645,"score_spread":0.210483767904652,"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."}}