{"id":"W2132617924","doi":"10.1093/jncimonographs/lgs005","title":"Multilevel Factors Affecting Quality: Examples From the Cancer Care Continuum","year":2012,"lang":"en","type":"article","venue":"JNCI Monographs","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research","funders":"National Cancer Institute; Ontario Ministry of Research and Innovation; Ontario Institute for Cancer Research; U.S. Department of Health and Human Services","keywords":"Psychological intervention; Medicine; Context (archaeology); Survivorship curve; Intervention (counseling); Diversity (politics); Multilevel model; Quality (philosophy); Risk analysis (engineering); Population; Management science; Nursing; Applied psychology; Psychology; Environmental health; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0005303471,0.0002807632,0.0005539092,0.0001130208,0.0003061361,0.0001340782,0.000411623,0.0001747592,0.0005339191],"category_scores_gemma":[0.0002414814,0.0002425449,0.000315385,0.0001838133,0.0001195829,0.0005896584,0.00009903203,0.0002654978,0.0001596099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001528592,"about_ca_system_score_gemma":0.00002763432,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01791485,"about_ca_topic_score_gemma":0.002536706,"domain_scores_codex":[0.9981583,0.00003480334,0.000670505,0.0004176445,0.00004632449,0.0006724521],"domain_scores_gemma":[0.9982966,0.000379913,0.0005537459,0.0005390362,0.00004534624,0.000185311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001258021,0.00003099551,0.9715751,0.00001191824,0.00009599605,1.770681e-7,0.0129332,0.000005609204,0.00003122728,0.006213761,0.003010751,0.006078671],"study_design_scores_gemma":[0.0004108303,0.00001616681,0.8937306,0.00002121388,0.00001569176,1.876391e-7,0.003914026,0.00001329474,0.0004176834,0.001863233,0.09924055,0.0003565254],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619048,0.026994,0.0007510614,0.0001937362,0.002085301,0.0002948414,0.001508251,0.00007802371,0.006190018],"genre_scores_gemma":[0.9970742,0.0005942036,0.0003691829,0.0006693295,0.0009335735,0.00005085639,0.00006170525,0.00004751381,0.0001993726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0962298,"threshold_uncertainty_score":0.9890695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1017677646964889,"score_gpt":0.2971350653451036,"score_spread":0.1953673006486147,"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."}}