{"id":"W7036925869","doi":"","title":"DBCG RT Nation Automation:National consistency in delineations in breast cancer patients","year":2024,"lang":"en","type":"dissertation","venue":"","topic":"Innovations in Educational Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Particle Physics","funders":"","keywords":"Breast cancer; Consistency (knowledge bases); Cancer; Stage (stratigraphy); MEDLINE","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":[0.02686862,0.0001751707,0.0003837214,0.002710657,0.0006963839,0.002369803,0.001080119,0.0007261384,0.01074675],"category_scores_gemma":[0.1356904,0.0003239126,0.0004827545,0.002884886,0.000594423,0.001457917,0.002589717,0.0008514415,0.002241536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002520797,"about_ca_system_score_gemma":0.003766374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02496723,"about_ca_topic_score_gemma":0.02038315,"domain_scores_codex":[0.9883133,0.007143419,0.0011465,0.001246174,0.001769999,0.000380597],"domain_scores_gemma":[0.9108661,0.06019403,0.007172005,0.00734532,0.01257673,0.001845878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002110189,0.0003692637,0.6954677,0.0001778331,0.0001743956,0.00006448736,0.00272826,0.001701265,0.0006324365,0.001954305,0.04748486,0.2471349],"study_design_scores_gemma":[0.0003933517,0.000478112,0.9521884,0.0003075994,0.0003197214,0.000194405,0.004561587,0.0104204,0.002991982,0.001680058,0.0263902,0.00007418394],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9242235,0.001398611,0.007645533,0.00547719,0.0006015662,0.0005318386,0.01129803,0.00081506,0.04800874],"genre_scores_gemma":[0.9712125,0.0003928263,0.0140284,0.0006056639,0.000164865,0.0003499599,0.007372015,0.0003489973,0.005524734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02686862,"threshold_uncertainty_score":0.1420965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04222836713074427,"score_gpt":0.4529975245761607,"score_spread":0.4107691574454164,"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."}}