{"id":"W2042758325","doi":"10.1055/s-2006-946656","title":"The role of simulators, models, phantoms. Where's the evidence?","year":2006,"lang":"en","type":"article","venue":"Endoscopy","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medicine; Learning curve; Medical physics; Radiology; Computer science","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":[0.000140686,0.0001022851,0.000154246,0.00001594238,0.0001235571,0.00001995444,0.0001183799,0.00003096033,0.00005414528],"category_scores_gemma":[0.00002013709,0.00004625562,0.00009526775,0.0001014215,0.000083441,0.00006380354,0.00002638959,0.00007736892,0.00001917569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008953338,"about_ca_system_score_gemma":0.00007985831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001342917,"about_ca_topic_score_gemma":0.0002130862,"domain_scores_codex":[0.9991912,0.0000336581,0.0001828014,0.0001417155,0.0002689236,0.0001817604],"domain_scores_gemma":[0.9990704,0.000363065,0.00007336101,0.0004001928,0.00005585904,0.00003714487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001247561,0.001533516,0.7609817,0.0002338852,0.001011599,0.00005607105,0.001677549,0.005425488,0.008435045,0.0889403,0.07669064,0.05376659],"study_design_scores_gemma":[0.007384545,0.001645311,0.06685836,0.002474136,0.001513343,0.00002334425,0.001157568,0.02744593,0.4078861,0.05825247,0.4248352,0.0005235972],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7839507,0.1890724,0.00009445434,0.008541388,0.0003820172,0.001011965,0.00001366192,0.00007666463,0.01685666],"genre_scores_gemma":[0.9962108,0.002605267,0.0001423785,0.00009937135,0.0002089797,0.0000620521,0.0000026244,0.00001374673,0.0006548559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6941234,"threshold_uncertainty_score":0.2030097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01309739208310842,"score_gpt":0.2843954123677067,"score_spread":0.2712980202845982,"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."}}