{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003464385,0.0008530242,0.0005172495,0.002245109,0.0005263509,0.0009895765,0.0009342164,0.0007689712,0.001287506],"category_scores_gemma":[0.01521723,0.0002372459,0.0009440819,0.001773211,0.0003637097,0.001042849,0.0007070077,0.0007598204,0.0009871997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201894,"about_ca_system_score_gemma":0.001194936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0164735,"about_ca_topic_score_gemma":0.01804983,"domain_scores_codex":[0.997492,0.001115863,0.0002879289,0.0005059052,0.0004796749,0.0001187059],"domain_scores_gemma":[0.987593,0.008136055,0.0007843723,0.0006995883,0.00257354,0.0002134248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002894591,0.003137076,0.3064371,0.004495432,0.0008354163,0.002541555,0.004973461,0.03096458,0.03003982,0.002701685,0.06219286,0.5487865],"study_design_scores_gemma":[0.0003771638,0.001288438,0.2303233,0.0003128125,0.0005437108,0.001655564,0.003346511,0.6955791,0.02565743,0.00134487,0.03942734,0.0001438771],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9433373,0.001521037,0.03247761,0.0006646061,0.0001852673,0.001376751,0.01470508,0.002035275,0.003697143],"genre_scores_gemma":[0.8599604,0.000568694,0.09668863,0.0002821393,0.0001107463,0.001161125,0.03833,0.0001169824,0.002781229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0164735,"threshold_uncertainty_score":0.03275526,"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."}}