{"id":"W4398142733","doi":"10.2196/52577","title":"“Notification! You May Have Cancer.” Could Smartphones and Wearables Help Detect Cancer Early?","year":2024,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Cancer Research UK; Barts Charity","keywords":"Wearable computer; Context (archaeology); Wearable technology; Health care; Computer science; Risk analysis (engineering); Unintended consequences; Internet privacy; Data science; Psychology; Medicine; Political science","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":[0.004705504,0.0005077987,0.0003853468,0.000944215,0.001799622,0.003386658,0.0009240439,0.004141126,0.01887084],"category_scores_gemma":[0.02196805,0.0002435055,0.0009425495,0.0005580051,0.001762451,0.006632135,0.002082895,0.004202627,0.007326235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101714,"about_ca_system_score_gemma":0.001871938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002899479,"about_ca_topic_score_gemma":0.005846381,"domain_scores_codex":[0.9968028,0.002092642,0.0001704105,0.0002154657,0.0004623862,0.0002562743],"domain_scores_gemma":[0.9914329,0.005272196,0.0007605853,0.0002408939,0.001503742,0.0007897048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001317225,0.0001007822,0.005154246,0.001137092,0.00003285313,0.0009494417,0.006456216,0.0001237814,0.0006511222,0.02023101,0.6962175,0.2688142],"study_design_scores_gemma":[0.0000231367,0.0001458087,0.002501311,0.001422378,0.00003173954,0.001616708,0.007277561,0.0002021849,0.0003916277,0.006457869,0.9798663,0.00006327686],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006276408,0.02426415,0.008065975,0.8667414,0.02722365,0.0001590224,0.0003339526,0.000493887,0.0664416],"genre_scores_gemma":[0.1389449,0.07644254,0.01584938,0.637502,0.03181109,0.0004061921,0.0005634829,0.0002734681,0.09820706],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.01887084,"threshold_uncertainty_score":0.06312925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06268529280993251,"score_gpt":0.4735881040820005,"score_spread":0.410902811272068,"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."}}