{"id":"W4406650183","doi":"10.1088/1361-6455/adac94","title":"Finding and minimizing systematic errors in dual-comb spectroscopy","year":2025,"lang":"en","type":"article","venue":"Journal of Physics B Atomic Molecular and Optical Physics","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"InterDigital (Canada); Université Laval","funders":"Communications Technology Laboratory; Natural Sciences and Engineering Research Council of Canada","keywords":"Dual (grammatical number); Spectroscopy; Computer science; Materials science; Physics; Linguistics; Philosophy; Astronomy","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":[0.008633544,0.0007769135,0.0008896447,0.002088018,0.0007271338,0.001384582,0.001255297,0.001274645,0.001042887],"category_scores_gemma":[0.02823585,0.0006297577,0.0003403089,0.001157072,0.001015179,0.001564144,0.00184541,0.001040782,0.000698984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006005407,"about_ca_system_score_gemma":0.001115845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004211176,"about_ca_topic_score_gemma":0.0007541699,"domain_scores_codex":[0.9917547,0.002500247,0.0004962988,0.001286636,0.003727031,0.0002351145],"domain_scores_gemma":[0.9829799,0.008450045,0.002285008,0.002500421,0.003555561,0.0002289894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008223827,0.0004282143,0.02266758,0.001466331,0.0003051901,0.0003705481,0.0008050313,0.02302895,0.3980816,0.02357575,0.001987131,0.5264613],"study_design_scores_gemma":[0.00008112421,0.0006763282,0.01672276,0.0004033186,0.000207845,0.0009243112,0.0002916212,0.2165466,0.721441,0.02746197,0.01506577,0.0001774153],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1132564,0.003245708,0.8789927,0.0007197335,0.0002763061,0.0001589023,0.0001291753,0.001151767,0.002069267],"genre_scores_gemma":[0.439049,0.0008461447,0.5581167,0.0002194682,0.00007288229,0.0001510343,0.0001655333,0.0002697019,0.001109557],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008633544,"threshold_uncertainty_score":0.04565907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02254343304770652,"score_gpt":0.3477574490777595,"score_spread":0.325214016030053,"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."}}