{"id":"W2037349109","doi":"10.1364/aio.2013.am1b.2","title":"High-Performance Spectroscopy using Virtual Slit Optics","year":2013,"lang":"en","type":"article","venue":"Imaging and Applied Optics","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tornado Spectral Systems (Canada)","funders":"","keywords":"Hyperspectral imaging; Throughput; Spectrometer; Optics; Raman spectroscopy; Slit; Spectroscopy; Spectral resolution; Imaging spectrometer; Materials science; Spectral imaging; Computer science; Resolution (logic); Optoelectronics; Physics; Artificial intelligence; Telecommunications; Spectral line","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":[0.0001101532,0.000176384,0.000150042,0.00003808748,0.0001158427,0.00008779459,0.000206763,0.0001102455,0.0000377705],"category_scores_gemma":[0.00002884894,0.0001563697,0.00002803044,0.00009750301,0.0003406711,0.000006565777,0.0002372592,0.0002138342,0.0000175684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002156939,"about_ca_system_score_gemma":0.00003629281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001258286,"about_ca_topic_score_gemma":1.244066e-7,"domain_scores_codex":[0.9988276,0.000008493016,0.0001881916,0.0003413014,0.0002096663,0.0004246828],"domain_scores_gemma":[0.9994447,0.00001525986,0.00004217995,0.0002713573,0.00005671501,0.0001697472],"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":[0.00001911847,0.00003608912,0.0003544698,0.00001704681,0.00001271766,8.767182e-7,0.000006931326,0.00001725205,0.9932424,0.00168157,0.001095177,0.00351633],"study_design_scores_gemma":[0.000298312,0.0001091242,0.0001970059,0.000016526,0.00001118647,0.0000156465,0.00004832857,0.005641718,0.9909133,0.001105146,0.001413656,0.0002300418],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812399,0.000142553,0.01331623,0.0002144887,0.00007250953,0.0001668069,0.000004908883,0.00004610267,0.004796478],"genre_scores_gemma":[0.9242661,0.0004501005,0.07422931,0.0003576315,0.0003358327,0.00002708779,0.00003084544,0.00002734962,0.0002757294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06091308,"threshold_uncertainty_score":0.6376569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007281580374133895,"score_gpt":0.2723286569712445,"score_spread":0.2650470765971106,"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."}}