{"id":"W2046892950","doi":"10.1016/j.acra.2014.07.020","title":"Development of a Personalized Training System Using the Lung Image Database Consortium and Image Database Resource Initiative Database","year":2014,"lang":"en","type":"article","venue":"Academic Radiology","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Cure Brain Cancer Foundation; Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Database; Computer science; Resource (disambiguation); Information retrieval","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":[0.002848203,0.0006535212,0.001145194,0.002392345,0.0006612061,0.001462141,0.00290959,0.0008130361,0.006355437],"category_scores_gemma":[0.006310449,0.0007084673,0.0007030449,0.001878219,0.0002056883,0.002506706,0.001616258,0.001363672,0.003937075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007278402,"about_ca_system_score_gemma":0.001515224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007482397,"about_ca_topic_score_gemma":0.004729105,"domain_scores_codex":[0.9982032,0.0002205602,0.0002619197,0.0005801014,0.0005889973,0.0001452429],"domain_scores_gemma":[0.9966295,0.000752811,0.00019897,0.0009414796,0.001090403,0.0003867297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001631628,0.001904423,0.03550972,0.0005299304,0.0004182311,0.000895967,0.0004089068,0.008960409,0.04662017,0.002634838,0.2357644,0.6647214],"study_design_scores_gemma":[0.0009617078,0.0007771924,0.07227509,0.0002271293,0.000532506,0.001962985,0.0006218589,0.5621434,0.1749165,0.004426456,0.1807555,0.0003996876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1240564,0.0007212833,0.4353909,0.001629612,0.000425806,0.00293802,0.03681471,0.389509,0.008514245],"genre_scores_gemma":[0.3464645,0.0004248835,0.5121273,0.001136614,0.0001594118,0.001321721,0.1239651,0.004952444,0.009447923],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007482397,"threshold_uncertainty_score":0.02126104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05860192423695923,"score_gpt":0.3379624842582519,"score_spread":0.2793605600212927,"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."}}