{"id":"W4403351515","doi":"10.1002/mp.17445","title":"Prediction of electron‐solid interaction parameters using machine learning","year":2024,"lang":"en","type":"article","venue":"Medical Physics","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Random forest; Mean squared error; Mean absolute percentage error; Computer science; Machine learning; Ensemble learning; Support vector machine; Artificial intelligence; Data mining; Statistics; Mathematics; Artificial neural network","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":[0.001702397,0.00110165,0.0008959933,0.002114759,0.0002901747,0.0008580217,0.001067243,0.001158912,0.001021631],"category_scores_gemma":[0.003755947,0.000294104,0.001031005,0.001077048,0.0003094424,0.0008834856,0.0004461816,0.0008876502,0.0005106547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006839806,"about_ca_system_score_gemma":0.0007066433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003038349,"about_ca_topic_score_gemma":0.002448405,"domain_scores_codex":[0.9995381,0.0001212063,0.00002994233,0.000146291,0.000113879,0.00005067523],"domain_scores_gemma":[0.9975642,0.001531913,0.0002323643,0.0001528351,0.0004653729,0.00005334821],"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":[0.0001211504,0.0002182131,0.01229877,0.00009858672,0.00008707785,0.00006172589,0.00001756251,0.9188085,0.002243724,0.0004713471,0.001639465,0.06393383],"study_design_scores_gemma":[0.000001973268,0.000009478076,0.0004823373,0.000003775494,0.000003668272,0.000004409224,0.000002742082,0.9984022,0.0007717477,0.0002047625,0.0001103216,0.000002705828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6255769,0.002324633,0.3622957,0.0005151987,0.0001440212,0.0001289221,0.002386527,0.003529712,0.003098422],"genre_scores_gemma":[0.9475552,0.0002114994,0.04870303,0.00006694086,0.00003661043,0.0000892381,0.002434933,0.00004921311,0.0008532991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003038349,"threshold_uncertainty_score":0.009003222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02763282625732414,"score_gpt":0.3137440704176535,"score_spread":0.2861112441603293,"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."}}