{"id":"W4406856422","doi":"10.2196/64611","title":"Leveraging Patient-Reported Outcome Measures for Optimal Dose Selection in Early Phase Cancer Trials","year":2025,"lang":"en","type":"review","venue":"JMIR Cancer","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preprint; Selection (genetic algorithm); Outcome (game theory); Phase (matter); Cancer; Computer science; Medicine; Medical physics; Oncology; Artificial intelligence; Internal medicine; Mathematics; World Wide Web; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007424368,0.0007490487,0.006951558,0.0004605163,0.0001047343,0.0001067053,0.0003736643,0.0008038118,0.0004410105],"category_scores_gemma":[0.1061237,0.0005831867,0.001450824,0.0008942615,0.00007311742,0.00008838245,0.0001051222,0.000911492,0.000004467714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001081014,"about_ca_system_score_gemma":0.001541583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002501435,"about_ca_topic_score_gemma":0.00008708657,"domain_scores_codex":[0.9893104,0.002736385,0.005627851,0.001046529,0.0006194391,0.0006593332],"domain_scores_gemma":[0.9419886,0.05420719,0.002835572,0.000452832,0.0003576225,0.0001581738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003726251,0.0003081895,0.00003202898,0.02103688,0.0007432707,0.00001094169,0.0001196897,0.000009369922,0.000002113603,0.0005433999,0.003501182,0.9733203],"study_design_scores_gemma":[0.008396046,0.0003534786,0.00001453823,0.04165548,0.006582185,0.000004594805,0.00001851826,0.00008260548,0.00003479132,0.04539527,0.8961788,0.0012837],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008436124,0.9314849,0.04987649,0.00007692433,0.003600481,0.01311419,0.00144384,0.0001805532,0.0001383126],"genre_scores_gemma":[0.00001690204,0.8531076,0.1178093,0.0001106686,0.001190737,0.02666846,0.00001454801,0.0001497413,0.0009319953],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9720366,"threshold_uncertainty_score":0.999662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8250779505726163,"score_gpt":0.6898320039324328,"score_spread":0.1352459466401835,"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."}}