{"id":"W2943093032","doi":"10.3747/co.26.4131","title":"Personalizing Post-Treatment Cancer Care: A Cross-Sectional Survey of the Needs and Preferences of Well Survivors of Breast Cancer","year":2019,"lang":"en","type":"article","venue":"Current Oncology","topic":"Cancer survivorship and care","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"","keywords":"Medicine; Logistic regression; Family medicine; Patient satisfaction; Breast cancer; Cross-sectional study; Confidentiality; Descriptive statistics; Nursing; Cancer; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001108107,0.0001514362,0.0002081056,0.0005294495,0.0004038365,0.0004814512,0.0002007626,0.0004290532,0.001624375],"category_scores_gemma":[0.002488365,0.0002157553,0.0002589093,0.0005909236,0.0002784124,0.0005533706,0.0004813984,0.0005341015,0.0002663166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003243044,"about_ca_system_score_gemma":0.0003436332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005343582,"about_ca_topic_score_gemma":0.007808434,"domain_scores_codex":[0.9995105,0.0001808328,0.00006358154,0.00004978645,0.0000998629,0.00009535129],"domain_scores_gemma":[0.9978743,0.0004492505,0.0009314236,0.00006700195,0.0002676962,0.000410371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003547152,0.0001493911,0.9948351,0.00002592149,0.00001969096,0.00005469998,0.002368071,0.00002698135,0.0003759298,0.00001042904,0.0001445935,0.001953663],"study_design_scores_gemma":[0.000003508507,0.0003119442,0.9932991,0.000009826816,0.000008913955,0.0001398617,0.005755524,0.00009520559,0.0000795785,0.000006771452,0.0002853991,0.000004244095],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999611,0.00002647548,0.00002501094,0.00003534549,0.000001248622,0.00001488385,0.0001536476,0.000001066314,0.0001314313],"genre_scores_gemma":[0.9994265,0.0000585325,0.00006400928,0.00006698124,0.000002112255,0.00002637283,0.000190073,7.356317e-7,0.0001646194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005343582,"threshold_uncertainty_score":0.01062495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0863681250130544,"score_gpt":0.3954693135233652,"score_spread":0.3091011885103108,"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."}}