{"id":"W4410488759","doi":"10.2196/71102","title":"Understanding Cancer Survivorship Care Needs Using Amazon Reviews: Content Analysis, Algorithm Development, and Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; U.S. National Library of Medicine; National Human Genome Research Institute; National Institute on Aging","keywords":"Preprint; Survivorship curve; Amazon rainforest; Cancer; Psychology; World Wide Web; Computer science; Medicine; Biology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0003381754,0.0002676006,0.0006858642,0.0006127759,0.0002204653,0.00007604014,0.00008636758,0.0001032994,0.000145778],"category_scores_gemma":[0.0000162246,0.0002365298,0.0001417022,0.001988681,0.00004808925,0.0001153276,0.00006692391,0.00020377,0.000001441813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001832986,"about_ca_system_score_gemma":0.0004219776,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0143124,"about_ca_topic_score_gemma":0.05781718,"domain_scores_codex":[0.9983311,0.000133576,0.0004693643,0.0004275315,0.0003310616,0.0003074035],"domain_scores_gemma":[0.9991491,0.0000407071,0.0001680122,0.0002952589,0.0002202588,0.0001266445],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001161335,0.00008936261,0.9228858,0.0006031301,0.001375334,0.000008877975,0.01862064,0.00004665245,0.0002371873,0.00006440454,0.0002093357,0.05574312],"study_design_scores_gemma":[0.008069905,0.0003593976,0.6270698,0.004844667,0.01339118,0.000006563431,0.2569447,0.00193491,0.005802346,0.00006214482,0.07977041,0.001744048],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9553367,0.03020547,0.0104735,0.00027369,0.0009289608,0.001942603,0.00003628317,0.0000759674,0.000726827],"genre_scores_gemma":[0.9959437,0.001354736,0.0002212726,0.0004546238,0.0001673694,0.0006306667,0.00005371498,0.00002420399,0.00114968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2958161,"threshold_uncertainty_score":0.9922514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2495291075795331,"score_gpt":0.4012338841947932,"score_spread":0.1517047766152601,"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."}}