{"id":"W2930763275","doi":"10.2196/12317","title":"Designing and Testing Apps to Support Patients With Cancer: Looking to Behavioral Science to Lead the Way","year":2019,"lang":"en","type":"article","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lead (geology); Psychology; Computer science; Data science; Risk analysis (engineering); Medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002094958,0.0001674725,0.0002186495,0.0001313908,0.0001801418,0.00007898538,0.0001877135,0.00003276517,0.0001510638],"category_scores_gemma":[0.00002560821,0.0001125133,0.00002213554,0.0009506415,0.00007100144,0.0001259622,0.0001365787,0.0001538945,0.0000348485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003865934,"about_ca_system_score_gemma":0.0004119156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005079628,"about_ca_topic_score_gemma":0.005770415,"domain_scores_codex":[0.9983216,0.00001225715,0.0001516455,0.0004758835,0.0005722451,0.0004663496],"domain_scores_gemma":[0.9989556,0.0000336994,0.00004938884,0.0003173962,0.0003231618,0.0003207305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001918589,0.00002579182,0.8534626,0.00004181024,0.000007312912,0.000003905833,0.005975388,0.0001331214,0.01008461,0.000003873741,0.0007392084,0.1293305],"study_design_scores_gemma":[0.001312409,0.002277386,0.9526124,0.001261911,0.00009145573,0.000006996033,0.002236396,0.00003840496,0.01335039,0.000001900356,0.02632149,0.000488851],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959139,0.00008156457,0.00009791304,0.0008992007,0.0004583154,0.001562641,0.00002253457,0.00004413134,0.0009197911],"genre_scores_gemma":[0.9941007,0.000002858051,0.0005426846,0.003567203,0.000171739,0.0006451082,0.000002096334,0.00003161031,0.0009359437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1288416,"threshold_uncertainty_score":0.7678913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03129663894970414,"score_gpt":0.3287811462168869,"score_spread":0.2974845072671828,"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."}}