{"id":"W2964366099","doi":"10.1002/mp.13744","title":"On calculating kerma, collision kerma and radiative yields","year":2019,"lang":"en","type":"article","venue":"Medical Physics","topic":"Radiation Therapy and Dosimetry","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Carleton University","funders":"","keywords":"Kerma; Collision; Dosimetry; Radiative transfer; Physics; Nuclear physics; Nuclear medicine; Optics; Computer science; Medicine","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":[0.0001757704,0.0001026552,0.0002242153,0.00002955591,0.00005319553,0.000009688564,0.0000445098,0.0001306871,0.0004493103],"category_scores_gemma":[0.0002240462,0.00007972659,0.00005250756,0.0001589348,0.00005935759,0.00005736155,0.00001978959,0.0003001609,0.0001815658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003510938,"about_ca_system_score_gemma":0.00007187708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001007368,"about_ca_topic_score_gemma":2.700189e-7,"domain_scores_codex":[0.9989554,0.00003499815,0.0001580467,0.0001869181,0.0005132884,0.0001513408],"domain_scores_gemma":[0.9991811,0.0003462819,0.00005323214,0.0001623207,0.00002949836,0.0002275664],"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":[0.00170701,0.001759875,0.2984216,0.0006004494,0.0005617972,0.0002300944,0.00569295,0.000838813,0.004652175,0.03762979,0.0312197,0.6166857],"study_design_scores_gemma":[0.03655375,0.006139288,0.5858318,0.002560665,0.0003476366,0.0001332531,0.0005879431,0.2255344,0.08376911,0.02816409,0.0285965,0.001781516],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889228,0.0001594385,0.00181986,0.001434173,0.0002333065,0.0002343205,0.00000368991,0.00004223535,0.007150211],"genre_scores_gemma":[0.9938732,0.00004366138,0.00005266453,0.005093607,0.0003645971,0.000003989629,0.00001976642,0.00001409406,0.0005344011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6149042,"threshold_uncertainty_score":0.4919633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039019545609365,"score_gpt":0.2804882813852176,"score_spread":0.270098085929124,"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."}}