{"id":"W7071671934","doi":"","title":"Some new computational methods in high-dimensional statistical learning in biostatistics","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Biostatistics; Statistical learning; Statistical analysis; Statistical model; Feature (linguistics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01162004,0.001381049,0.002087439,0.002380216,0.001128121,0.002780897,0.003422458,0.001818429,0.008388612],"category_scores_gemma":[0.04163785,0.001425505,0.002731093,0.004037297,0.003466384,0.004002614,0.003600858,0.005305925,0.002242272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206818,"about_ca_system_score_gemma":0.001650799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002339987,"about_ca_topic_score_gemma":0.003228325,"domain_scores_codex":[0.9941655,0.003441212,0.0004548726,0.0005916422,0.001236844,0.0001099217],"domain_scores_gemma":[0.9668097,0.02736888,0.0005083592,0.002293949,0.002465877,0.0005532398],"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":[0.00006164103,0.0001306146,0.001076032,0.0006684976,0.0002324701,0.000142654,0.0002826434,0.07304817,0.001093679,0.6218923,0.02554529,0.2758261],"study_design_scores_gemma":[0.00003320045,0.00002864876,0.0004864012,0.00008150181,0.00006748224,0.0001463561,0.00002783428,0.4533412,0.0007336172,0.5271084,0.01789159,0.00005366809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004993586,0.001063875,0.9967269,0.0005547873,0.000209079,0.00001971041,0.00004311139,0.00008683586,0.0007962828],"genre_scores_gemma":[0.01666066,0.002921869,0.9713841,0.0007120633,0.001297997,0.000504718,0.0003084647,0.0003044271,0.005905631],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01162004,"threshold_uncertainty_score":0.0614534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02595892979567063,"score_gpt":0.3236612293358971,"score_spread":0.2977022995402265,"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."}}