{"id":"W2911310511","doi":"10.6084/m9.figshare.8865995","title":"Split Regularized Regression","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Regression; Statistics; Regression analysis; Computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008501212,0.002166474,0.002382578,0.002584256,0.0007427067,0.002393016,0.004762452,0.002470233,0.01186809],"category_scores_gemma":[0.02822593,0.0007437741,0.002670253,0.003370312,0.00120855,0.002427141,0.002742486,0.003479659,0.009472009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001094402,"about_ca_system_score_gemma":0.001752537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003806074,"about_ca_topic_score_gemma":0.007079947,"domain_scores_codex":[0.993977,0.003670845,0.0002509181,0.001348934,0.0005403217,0.0002119202],"domain_scores_gemma":[0.9926879,0.003078355,0.0005105779,0.002714485,0.0008493731,0.0001591959],"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":[0.001415615,0.0005821363,0.01657741,0.001217279,0.001285311,0.0003648156,0.000298388,0.2726744,0.002208665,0.06104527,0.2933282,0.3490025],"study_design_scores_gemma":[0.0004239738,0.0001643024,0.003360573,0.0001726923,0.0001572442,0.0002269537,0.00008883948,0.7953517,0.00181328,0.1327396,0.0654166,0.00008419113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.01440176,0.001867148,0.9291985,0.001609543,0.0003625265,0.0003719167,0.04011675,0.007941005,0.004130804],"genre_scores_gemma":[0.1387566,0.001074225,0.7343609,0.001777541,0.0003895464,0.001799586,0.1110067,0.002108924,0.008725967],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01186809,"threshold_uncertainty_score":0.04495925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2109463554224679,"score_gpt":0.4229597377464969,"score_spread":0.2120133823240289,"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."}}