{"id":"W4237439689","doi":"10.1038/labinvest.2008.153","title":"Special Category - Pan-genomic/Pan-proteomic Approaches to Cancer","year":2009,"lang":"en","type":"article","venue":"Laboratory Investigation","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cancer; Computational biology; Biology; Genetics; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001089803,0.0002209614,0.0001865735,0.00006741822,0.0001863162,0.00005992657,0.000272984,0.0001721722,0.0001931271],"category_scores_gemma":[0.00003277702,0.0002426938,0.00004221667,0.000365329,0.00007991103,0.0001982778,0.00003663795,0.0002526556,0.0000899303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002725506,"about_ca_system_score_gemma":0.0002105847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004785587,"about_ca_topic_score_gemma":0.00002538745,"domain_scores_codex":[0.9987872,0.00001893412,0.0003129126,0.0004437127,0.0001587415,0.0002784881],"domain_scores_gemma":[0.9991075,0.00001316718,0.0001640646,0.0004551534,0.00008053591,0.0001795595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000185545,0.00003336898,0.001075568,0.00002384023,0.000008915231,0.000001126083,0.0003895657,0.0002135397,0.9612654,0.02210603,0.005270631,0.009593452],"study_design_scores_gemma":[0.0001888347,0.00002558988,0.002859868,0.00003390371,0.00001900588,9.613319e-7,0.0000700437,0.0001179556,0.932964,0.03058498,0.03276865,0.0003661959],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872038,0.00008766361,0.002123923,0.002844395,0.0000987873,0.0004875067,0.0001616789,0.0003648679,0.006627348],"genre_scores_gemma":[0.9492325,0.00005008266,0.04253715,0.002209706,0.004088024,0.0008887695,0.0001595603,0.00005431669,0.0007798455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04041323,"threshold_uncertainty_score":0.9896765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0477373312472261,"score_gpt":0.2653959853624235,"score_spread":0.2176586541151974,"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."}}