{"id":"W4289780846","doi":"10.2196/35798","title":"Moving to Personalized Medicine Requires Personalized Health Plans","year":2022,"lang":"en","type":"article","venue":"Journal of Participatory Medicine","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Financial plan; Health care; Plan (archaeology); Health plan; Business; Process (computing); Personalized medicine; Actuarial science; Selection (genetic algorithm); Population; Marketing; Finance; Medicine; Computer science; Economics","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","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.0538078,0.0002593935,0.002210266,0.0009324892,0.0005944238,0.0000159032,0.0005358233,0.00005814116,0.008620738],"category_scores_gemma":[0.008411413,0.0002572033,0.0001794553,0.0004841685,0.0002961982,0.0002854642,0.00009891584,0.0005443139,0.0001639483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001531207,"about_ca_system_score_gemma":0.000553566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007857808,"about_ca_topic_score_gemma":0.0000690887,"domain_scores_codex":[0.9900067,0.001364992,0.006904579,0.0004281051,0.0006065241,0.0006891399],"domain_scores_gemma":[0.9926773,0.001243544,0.004585033,0.0004202844,0.0001589611,0.0009149105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005085026,0.000281902,0.03750219,0.0005186658,0.0003901944,0.00007176979,0.1109593,0.001446036,0.0002137356,0.08624264,0.7613783,0.000486778],"study_design_scores_gemma":[0.00849776,0.004636159,0.01996596,0.0007917664,0.00007277029,0.0003693752,0.05824707,0.002271897,0.000005885324,0.00647265,0.8981276,0.0005411021],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4537146,0.02108388,0.005417502,0.5144387,0.003336555,0.0006868039,0.0001538471,0.00004403034,0.001124101],"genre_scores_gemma":[0.8748924,0.0002869218,0.001388608,0.1179475,0.003216745,0.0001226486,0.00001951081,0.00007292348,0.002052831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4211777,"threshold_uncertainty_score":0.999988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5981866793203227,"score_gpt":0.513485438742357,"score_spread":0.08470124057796569,"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."}}