{"id":"W3211251719","doi":"10.1101/2021.10.31.21265690","title":"Estimating treatment effect for individuals with progressive multiple sclerosis using deep learning","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"NeuroRx Research (Canada); Mila - Quebec Artificial Intelligence Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Medicine; Clinical trial; Multiple sclerosis; Leverage (statistics); Internal medicine; Oncology; Machine learning; Immunology; Computer science","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":[0.02581268,0.001117783,0.002313657,0.0009756967,0.0003877634,0.0009700971,0.001150023,0.001486196,0.003268774],"category_scores_gemma":[0.04462954,0.0003937024,0.003413814,0.0006600536,0.001075483,0.001036255,0.001205481,0.003671605,0.0004009005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008410091,"about_ca_system_score_gemma":0.0009990599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002352409,"about_ca_topic_score_gemma":0.002515761,"domain_scores_codex":[0.9898325,0.007788782,0.0003779523,0.001266785,0.0004183772,0.0003155503],"domain_scores_gemma":[0.9340887,0.05947555,0.002480491,0.002593193,0.0006595255,0.0007025401],"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":[0.0286349,0.001792133,0.3014277,0.001744049,0.01391618,0.0006297296,0.0002234529,0.3721749,0.005968024,0.005509445,0.01048042,0.257499],"study_design_scores_gemma":[0.003952883,0.005072438,0.07688001,0.0004619168,0.009837492,0.0004556099,0.0001057133,0.8450248,0.009298064,0.04294069,0.005833273,0.0001371636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.778848,0.009962489,0.1911338,0.007711952,0.0005851166,0.0005482411,0.005438417,0.00106875,0.004703206],"genre_scores_gemma":[0.9893818,0.0003129288,0.007461926,0.0008578776,0.0001191906,0.0001199767,0.001134322,0.0000265052,0.0005854718],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02581268,"threshold_uncertainty_score":0.1365122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5159298482799332,"score_gpt":0.5238606871304021,"score_spread":0.007930838850468969,"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."}}