{"id":"W2520501086","doi":"10.1016/j.cpet.2016.08.008","title":"Molecular Imaging and Precision Medicine in Lung Cancer","year":2016,"lang":"en","type":"review","venue":"PET Clinics","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Medicine; Precision medicine; Lung cancer; Biomarker; Disease; Cancer; Lung; Oncology; Internal medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002359016,0.0002450357,0.001179469,0.00018898,0.00002660082,0.000008159227,0.00006690602,0.00008272079,0.0001706678],"category_scores_gemma":[0.0002086808,0.0001402802,0.0001311923,0.0001631573,0.00006851497,0.00003878412,0.00005017978,0.0002249708,0.00001114992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002628112,"about_ca_system_score_gemma":0.0004447108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008473502,"about_ca_topic_score_gemma":0.00001765109,"domain_scores_codex":[0.9985936,0.00005986296,0.0005925218,0.0003829894,0.0001819573,0.0001890843],"domain_scores_gemma":[0.9989743,0.0003288546,0.0002206028,0.0002995899,0.00006001223,0.0001166773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006825615,0.00003007296,0.0007228653,0.004757459,0.0001532525,0.0002457168,0.0000594361,1.207373e-7,2.063205e-7,0.00005251223,0.001179488,0.9927921],"study_design_scores_gemma":[0.001367688,0.00004308181,0.0001095324,0.06578156,0.002381816,0.00008568766,0.000009710197,0.00004801496,1.237553e-7,0.00008849982,0.9299443,0.0001400006],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004385753,0.9955233,0.00006341217,0.001010096,0.0004333398,0.0008260878,0.00004972763,0.00002321622,0.002026992],"genre_scores_gemma":[0.00004646626,0.9981363,0.0001550716,0.0003002924,0.0002633734,0.0001775105,0.00007801973,0.00004883185,0.000794086],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9926521,"threshold_uncertainty_score":0.5720459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03263889956480497,"score_gpt":0.4809749719053772,"score_spread":0.4483360723405722,"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."}}