{"id":"W3214085745","doi":"10.5281/zenodo.4326594","title":"MATLAB functions for maximum-likelihood parameter estimation in terahertz time-domain spectroscopy","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Spectroscopy and Laser Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Maximum likelihood; Spectroscopy; MATLAB; Estimation theory; Time domain; Statistics; Mathematics; Computer science; Applied mathematics; Algorithm; Physics; Optics; Computational physics; Computer vision; Quantum mechanics","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":[0.001355111,0.002061926,0.000988249,0.00172077,0.0006343554,0.001178866,0.002200713,0.001386538,0.2026588],"category_scores_gemma":[0.006646106,0.001087882,0.0009153821,0.001183054,0.0004865672,0.00120865,0.001365613,0.002259875,0.08455229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000787371,"about_ca_system_score_gemma":0.001541343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002796344,"about_ca_topic_score_gemma":0.004889603,"domain_scores_codex":[0.9993293,0.0001219949,0.00007069079,0.0001062603,0.0002997391,0.00007210127],"domain_scores_gemma":[0.9975351,0.001394823,0.0002169186,0.0001714798,0.0005885049,0.00009318349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000483433,0.000299625,0.002178807,0.002625138,0.000267784,0.0009799622,0.0004875986,0.06532428,0.02032084,0.0313495,0.5122095,0.3634734],"study_design_scores_gemma":[0.0004658081,0.0001646428,0.002363914,0.0007012786,0.00009130966,0.001636648,0.0001378501,0.482951,0.04698549,0.04226181,0.4219904,0.0002498658],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.001725514,0.0006749486,0.8540508,0.0003542285,0.0001928285,0.0001953024,0.01186267,0.1183782,0.0125656],"genre_scores_gemma":[0.04197006,0.001744325,0.8240573,0.0008200515,0.0001916522,0.002079315,0.02042411,0.06367456,0.04503859],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2026588,"threshold_uncertainty_score":0.6779613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01975975112296103,"score_gpt":0.2459060483417518,"score_spread":0.2261462972187908,"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."}}