{"id":"W4386817860","doi":"10.1093/rpd/ncad152","title":"Electron paramagnetic resonance spectroscopy for the detection of radiation exposure in dreissenid mussels","year":2023,"lang":"en","type":"article","venue":"Radiation Protection Dosimetry","topic":"Radiation Effects and Dosimetry","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada; University Network of Excellence in Nuclear Engineering","keywords":"Electron paramagnetic resonance; Spectroscopy; Radiation; Dosimetry; Environmental science; SIGNAL (programming language); Materials science; Sampling (signal processing); Nuclear magnetic resonance; Analytical Chemistry (journal); Physics; Chemistry; Nuclear medicine; Computer science; Optics; Environmental chemistry; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008823322,0.000346145,0.0002426276,0.0006564792,0.0003390755,0.0003141153,0.0002486925,0.000457198,0.0004392354],"category_scores_gemma":[0.0009045923,0.0002304746,0.0001898526,0.000389133,0.0002632406,0.0002439714,0.0004938095,0.0004631346,0.0001436877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001923795,"about_ca_system_score_gemma":0.0002965092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001227232,"about_ca_topic_score_gemma":0.003648956,"domain_scores_codex":[0.9995959,0.0001330003,0.00002543594,0.0001135394,0.0001001972,0.00003191398],"domain_scores_gemma":[0.9995719,0.0001314762,0.00008502061,0.00005966643,0.0001070741,0.00004474873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005287212,0.00001110504,0.00220495,0.00005106287,0.000009938642,0.00001773788,0.00006403967,0.0002275309,0.9944081,0.0000275329,0.00001185871,0.002913192],"study_design_scores_gemma":[0.00001940554,0.001255373,0.1473324,0.0000481995,0.00009238681,0.0004828611,0.0002598798,0.004633137,0.8425751,0.000290235,0.002967214,0.00004373031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413558,0.00129812,0.05580218,0.00006503961,0.00001003043,0.0000618175,0.0003333414,0.0001809993,0.0008926871],"genre_scores_gemma":[0.9531846,0.001175542,0.04342862,0.00007494048,0.000007906401,0.00009957974,0.0003761932,0.00004333018,0.001609192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001227232,"threshold_uncertainty_score":0.004666269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144020820612031,"score_gpt":0.2376071698810271,"score_spread":0.2261669616749068,"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."}}