{"id":"W4413318947","doi":"10.31219/osf.io/dk6zv_v4","title":"Regularized cross-sectional network modeling with missing data: A comparison of methods","year":2025,"lang":"en","type":"article","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Missing data; Computer science; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.07880648,0.001684332,0.002497912,0.002425062,0.0008997588,0.002022598,0.005416946,0.002239642,0.004021882],"category_scores_gemma":[0.1324236,0.00133852,0.003376499,0.002314279,0.001403327,0.004788738,0.003758739,0.003433717,0.0006756822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001659175,"about_ca_system_score_gemma":0.002861122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005835984,"about_ca_topic_score_gemma":0.004367216,"domain_scores_codex":[0.9395834,0.05407429,0.001408825,0.002507452,0.001985329,0.0004406609],"domain_scores_gemma":[0.8112466,0.164001,0.005055989,0.01360199,0.005086721,0.001007625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003223929,0.0007897184,0.02133212,0.002056135,0.00524682,0.0001925657,0.001682527,0.4479232,0.0005349256,0.1223099,0.006318971,0.3883891],"study_design_scores_gemma":[0.000329841,0.0003439389,0.003578425,0.0004192751,0.0003335025,0.0001382326,0.0002472579,0.9193677,0.000475391,0.07001586,0.00464207,0.0001084146],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0167665,0.003185111,0.9770586,0.0008369558,0.0001283878,0.0004273762,0.0002805135,0.0003977286,0.0009188594],"genre_scores_gemma":[0.2514639,0.004707375,0.737414,0.000489976,0.0002666454,0.002296994,0.001235556,0.0004313531,0.001694215],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07880648,"threshold_uncertainty_score":0.4167735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.399867031956938,"score_gpt":0.5676503663249911,"score_spread":0.1677833343680531,"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."}}