{"id":"W3032973540","doi":"10.2196/17352","title":"Differences in Electronic Personal Health Information Tool Use Between Rural and Urban Cancer Patients in the United States: Secondary Data Analysis","year":2020,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Health Information National Trends Survey; Cancer; Medicine; Rural area; Logistic regression; Health care; Family medicine; Demography; Environmental health; Gerontology; Health information; Internal medicine; Economic growth; Pathology","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":[0.002618256,0.000286103,0.0007283898,0.003819064,0.0007032764,0.001063007,0.0006337801,0.0003975882,0.003667658],"category_scores_gemma":[0.00883588,0.0003433748,0.001395408,0.005427105,0.00044936,0.0008551251,0.001624094,0.0007945294,0.0006234035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009431972,"about_ca_system_score_gemma":0.001235895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01860967,"about_ca_topic_score_gemma":0.01567129,"domain_scores_codex":[0.9973857,0.0007135675,0.0005421339,0.0005409493,0.0005252087,0.0002924451],"domain_scores_gemma":[0.9914908,0.002284381,0.003369034,0.0006155856,0.001531339,0.0007089091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001534243,0.0000956264,0.9969021,0.00008222657,0.0001582851,0.00002888065,0.0003049216,0.00005971571,0.00006065818,0.00003004826,0.0007061415,0.001417973],"study_design_scores_gemma":[0.0000279234,0.0001684313,0.9975315,0.00003672871,0.00007619951,0.00008638786,0.00111029,0.0002903797,0.00007025159,0.00003565386,0.0005577516,0.000008457025],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987772,0.0001413537,0.000229108,0.00008795534,0.000006804681,0.0001543479,0.01073205,0.00001502794,0.0008613942],"genre_scores_gemma":[0.9897537,0.0001074933,0.0002559432,0.0001126385,0.00001022676,0.0004346555,0.009005558,0.00001074586,0.0003089535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01860967,"threshold_uncertainty_score":0.03700268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.038821411842043,"score_gpt":0.3136200161994961,"score_spread":0.2747986043574531,"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."}}