{"id":"W4411880349","doi":"10.1186/s13054-025-05515-3","title":"Missing the target in target trial emulation","year":2025,"lang":"en","type":"letter","venue":"Critical Care","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University of Toronto","funders":"","keywords":"Medicine; Emulation; Intensive care medicine; Missing data; Medical physics; Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.00219242,0.000424159,0.001263843,0.0001421187,0.0001646722,0.0001808517,0.0006290334,0.001655056,0.0009976699],"category_scores_gemma":[0.3721749,0.0003088028,0.0004018842,0.0003165139,0.0004368367,0.00005137839,0.0002068933,0.003708165,0.00003409305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000223001,"about_ca_system_score_gemma":0.0003007163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009784986,"about_ca_topic_score_gemma":0.000001570041,"domain_scores_codex":[0.9931371,0.00317847,0.001514993,0.0007194108,0.0007924044,0.0006576762],"domain_scores_gemma":[0.8423119,0.1563297,0.0001370612,0.0008182504,0.0003231013,0.00007997719],"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":[0.000931062,0.00006786824,0.00001322114,0.002372091,0.00003214653,0.0003231931,0.0002614263,0.00000136548,0.000002405764,0.05090378,0.9422454,0.002846039],"study_design_scores_gemma":[0.004203015,0.00009663042,0.000005818442,0.0004699014,0.0001815628,0.000001462079,0.00009885013,0.0001513577,0.00004823287,0.8549128,0.1395278,0.0003026612],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.00002771554,0.0004773334,0.1150503,0.8629289,0.006613137,0.002036573,0.0006835936,0.0001592,0.0120233],"genre_scores_gemma":[0.0007191151,0.00000352191,0.6877751,0.2996055,0.01088301,0.0002041626,0.0001001051,0.00008929712,0.0006201308],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.804009,"threshold_uncertainty_score":0.9999364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5411079281231422,"score_gpt":0.5948375086651048,"score_spread":0.05372958054196253,"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."}}