{"id":"W4393144933","doi":"10.32920/25474918.v1","title":"Social Media and mHealth Technology for Cancer Screening: Systematic Review and Meta-analysis","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; Cancer Care Ontario; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research","keywords":"mHealth; Meta-analysis; Social media; Data science; Medicine; Internet privacy; Psychology; Computer science; World Wide Web; Nursing; Internal medicine; Psychological intervention","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01963498,0.002946506,0.01957305,0.00866635,0.0007764661,0.003548439,0.002491481,0.002579903,0.005892124],"category_scores_gemma":[0.05544959,0.001649175,0.03443963,0.009432466,0.0009877397,0.002852533,0.001981699,0.002091725,0.0003910435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004733783,"about_ca_system_score_gemma":0.00701691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000448,"about_ca_topic_score_gemma":0.01861577,"domain_scores_codex":[0.9848428,0.00810313,0.003900035,0.0009685223,0.001776976,0.0004085471],"domain_scores_gemma":[0.9666278,0.02533168,0.004919577,0.0007446941,0.002026032,0.000350196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.001552725,0.0000447563,0.001894312,0.6065145,0.3748837,0.00008128407,0.00009982495,0.0003231923,0.00008985286,0.0001271384,0.0007281579,0.01366051],"study_design_scores_gemma":[0.001098564,0.000311506,0.003054189,0.07127935,0.9219555,0.00008348751,0.00006805843,0.0002026207,0.0001252491,0.0001866763,0.001608101,0.00002666391],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.003241559,0.9941876,0.0004812514,0.0002327748,0.0001679432,0.0009134085,0.0004665309,0.00002764737,0.0002812755],"genre_scores_gemma":[0.09518313,0.8952859,0.00298022,0.0008838053,0.0002670307,0.004337626,0.0006550881,0.00002649025,0.000380793],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01963498,"threshold_uncertainty_score":0.1038409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3937731211523726,"score_gpt":0.5286088785363537,"score_spread":0.1348357573839811,"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."}}