{"id":"W1979856353","doi":"10.1118/1.1355000","title":"Cascade analysis for medical imaging detectors with stages involving both amplification and dislocation processes","year":2001,"lang":"en","type":"article","venue":"Medical Physics","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cascade; Monte Carlo method; Detector; Formalism (music); Physics; Dislocation; Medical imaging; Statistical physics; Detective quantum efficiency; Optics; Computational physics; Computer science; Mathematics; Artificial intelligence; Statistics; Image quality; Chemistry; Image (mathematics); Condensed matter physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001640652,0.0001433898,0.0002021758,0.00004099665,0.0002243646,0.00007273298,0.0001653596,0.00003450618,0.0001185025],"category_scores_gemma":[0.00003779583,0.0001164635,0.00005860388,0.0006575423,0.0001472055,0.0001637969,0.00003959209,0.0001471416,0.000004151525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001621099,"about_ca_system_score_gemma":0.0001519688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001807003,"about_ca_topic_score_gemma":0.00004473761,"domain_scores_codex":[0.9987931,0.00001638008,0.0001996176,0.0003129947,0.0004573741,0.0002205546],"domain_scores_gemma":[0.9991643,0.0001829104,0.0001109361,0.0002013105,0.0001171239,0.0002233778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003276295,0.0005967339,0.5635642,0.0001333723,0.0006001992,0.000002005261,0.0007783627,0.0001084464,0.0004640449,0.04846093,0.0004917241,0.3847672],"study_design_scores_gemma":[0.008733659,0.0003898129,0.3749874,0.0009298245,0.004934809,0.00001798713,0.005167407,0.2454656,0.02087586,0.2865793,0.0476603,0.004258068],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.305845,0.00007718323,0.6922074,0.001153063,0.00001893834,0.0002443226,0.00002873503,0.00004954932,0.0003758854],"genre_scores_gemma":[0.9986287,0.00003326307,0.0002815435,0.0001346303,0.0005253336,0.0001370308,0.0001968291,0.00002468595,0.00003795708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6927838,"threshold_uncertainty_score":0.4749244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01012363796327576,"score_gpt":0.2647885860482623,"score_spread":0.2546649480849866,"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."}}