{"id":"W1986654598","doi":"10.1120/jacmp.v8i1.2324","title":"Evaluation of the analytical anisotropic algorithm in an extreme water–lung interface phantom using Monte Carlo dose calculations","year":2007,"lang":"en","type":"article","venue":"Journal of Applied Clinical Medical Physics","topic":"Advanced Radiotherapy Techniques","field":"Physics and Astronomy","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; BC Cancer Agency","funders":"Varian Medical Systems","keywords":"Imaging phantom; Monte Carlo method; Algorithm; Standard deviation; Radiation treatment planning; Convolution (computer science); Nuclear medicine; Beam (structure); Mathematics; Physics; Computational physics; Statistics; Computer science; Optics; Medicine; Radiation therapy; Artificial intelligence; Radiology","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":[0.00387735,0.0005117491,0.000460069,0.0007762109,0.0003191558,0.001185668,0.0009054319,0.0006267328,0.0004455041],"category_scores_gemma":[0.0137079,0.0003096564,0.0004172173,0.0008913797,0.0004366958,0.0006895077,0.0007129455,0.00053392,0.0001350657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009538284,"about_ca_system_score_gemma":0.001105611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003517592,"about_ca_topic_score_gemma":0.002810231,"domain_scores_codex":[0.9975722,0.0008435726,0.0001320157,0.0001654579,0.001198893,0.00008777897],"domain_scores_gemma":[0.9927119,0.004873554,0.0005547033,0.0005806271,0.00117697,0.0001023082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001252885,0.0002656311,0.01057408,0.0002373286,0.0001443832,0.0001398672,0.0004214651,0.7369578,0.05880413,0.007555948,0.0006051273,0.1830414],"study_design_scores_gemma":[0.00002418089,0.000219098,0.001915369,0.00001383748,0.00002985491,0.0001327948,0.00002856619,0.9759064,0.01996565,0.000566313,0.001167182,0.00003074265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1542604,0.0003763847,0.8410486,0.0001040388,0.00003180178,0.0001131351,0.00005350385,0.001134769,0.002877289],"genre_scores_gemma":[0.5616952,0.0001577793,0.4370816,0.0000520581,0.00001040082,0.00008671143,0.00007446723,0.000303378,0.0005385039],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00387735,"threshold_uncertainty_score":0.02050567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08837448990156496,"score_gpt":0.4417731544120682,"score_spread":0.3533986645105032,"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."}}