{"id":"W4406147515","doi":"10.1002/cam4.70554","title":"Can Large Language Models Aid Caregivers of Pediatric Cancer Patients in Information Seeking? A Cross‐Sectional Investigation","year":2025,"lang":"en","type":"article","venue":"Cancer Medicine","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"CLARITY; Readability; Credibility; Medicine; Cross-sectional study; Medical education; Psychology; Computer science; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.009369087,0.0003132937,0.0004233297,0.0009973979,0.0007103647,0.001154742,0.0004348468,0.0006281264,0.001504163],"category_scores_gemma":[0.03251195,0.0004697382,0.0005790275,0.0007397928,0.0005638666,0.001726859,0.001462749,0.001109673,0.0002823144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006488285,"about_ca_system_score_gemma":0.0009730462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002416084,"about_ca_topic_score_gemma":0.00318066,"domain_scores_codex":[0.9961928,0.002134759,0.0003947318,0.0003473169,0.0006012493,0.0003291202],"domain_scores_gemma":[0.9795861,0.01016248,0.005966831,0.0008219747,0.0025964,0.0008662637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001207984,0.0004408765,0.9783089,0.00010181,0.00004306547,0.0001680416,0.0125833,0.00004028809,0.0001506755,0.00003581579,0.0002753092,0.0077311],"study_design_scores_gemma":[0.00002812042,0.001542634,0.9565654,0.0002070961,0.0001019777,0.0009647215,0.03770982,0.0004783465,0.000379869,0.00007011501,0.001926118,0.00002581255],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99935,0.0001404443,0.0000791041,0.00006877495,0.000004018575,0.0000403372,0.00006482757,0.000001777752,0.0002506951],"genre_scores_gemma":[0.9990534,0.0002009955,0.0003250051,0.00008213255,0.000004995728,0.0001100664,0.0001078385,0.000002237793,0.0001133927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009369087,"threshold_uncertainty_score":0.0495491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01803542766032988,"score_gpt":0.3216729767487702,"score_spread":0.3036375490884403,"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."}}