{"id":"W2785517012","doi":"10.2196/medinform.8662","title":"Automated Information Extraction on Treatment and Prognosis for Non–Small Cell Lung Cancer Radiotherapy Patients: Clinical Study","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Topic Modeling","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Data extraction; Lung cancer; Radiation therapy; Information extraction; Recall; Medical physics; Computer science; Oncology; Internal medicine; MEDLINE; Information retrieval","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":[0.004609922,0.0005208032,0.0005613958,0.003740225,0.0003598215,0.0009246794,0.0005304374,0.0005443105,0.00232788],"category_scores_gemma":[0.01613391,0.0001637233,0.0008939978,0.002318043,0.0003435601,0.000890477,0.0009175299,0.0003132098,0.0008136072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004427719,"about_ca_system_score_gemma":0.001182038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001725006,"about_ca_topic_score_gemma":0.001752635,"domain_scores_codex":[0.9974076,0.0009519666,0.0005743719,0.0005768642,0.0003972762,0.00009184517],"domain_scores_gemma":[0.9896366,0.006141989,0.001152685,0.0009691356,0.001934836,0.0001646652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002059363,0.0007086383,0.348538,0.00304311,0.0004698581,0.001254885,0.001337591,0.005972556,0.01261033,0.0003643304,0.008299965,0.6153414],"study_design_scores_gemma":[0.001047595,0.003372999,0.7834793,0.001154587,0.002793067,0.005652788,0.002559442,0.07727933,0.06854527,0.002885777,0.05098773,0.0002420516],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9019069,0.005231762,0.0580602,0.0009396605,0.0001056369,0.001982623,0.02508417,0.002586901,0.004102136],"genre_scores_gemma":[0.8733878,0.001588433,0.08518099,0.0002127748,0.00008625424,0.001092203,0.03731181,0.00009777634,0.001042057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004609922,"threshold_uncertainty_score":0.02437991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0318367729255427,"score_gpt":0.3748708232248038,"score_spread":0.3430340502992611,"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."}}