{"id":"W2260032334","doi":"10.1038/ncomms11562","title":"Direct imaging of molecular symmetry by coherent anti-stokes Raman scattering","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; University of Bern; Aix-Marseille Université","keywords":"Raman scattering; Raman spectroscopy; X-ray Raman scattering; Symmetry (geometry); Coherent anti-Stokes Raman spectroscopy; Molecular physics; Anisotropy; Scattering; Materials science; Microscopy; Optics; Molecular vibration; Chemical imaging; Chemical physics; Chemistry; Physics; Computer science; Hyperspectral imaging","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":[0.0004176558,0.000559299,0.0002320817,0.000641156,0.0002354218,0.0006599995,0.0005146259,0.000456283,0.001151189],"category_scores_gemma":[0.000775309,0.0003292104,0.0002559205,0.0003137702,0.001015534,0.0007385581,0.0006305514,0.0005977907,0.0004751857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002821683,"about_ca_system_score_gemma":0.0004404039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003252689,"about_ca_topic_score_gemma":0.0005352566,"domain_scores_codex":[0.999451,0.0001089212,0.00002013358,0.0001200466,0.0002314773,0.00006844453],"domain_scores_gemma":[0.9992421,0.0002757738,0.0002141539,0.0001050789,0.0001127068,0.00005023603],"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":[0.00003481554,0.00001590112,0.0002133707,0.0000345362,0.000004209437,0.00002555514,0.00001960835,0.0002021845,0.9942629,0.001624696,0.00005881998,0.003503249],"study_design_scores_gemma":[0.000009106456,0.00005345846,0.0007189487,0.000003351916,0.000005170928,0.0000854765,0.00001837983,0.004850868,0.9930647,0.0005115193,0.0006672501,0.00001170846],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8781742,0.001215093,0.1144876,0.000202343,0.00009961155,0.00007789129,0.0003346689,0.0002077792,0.005200739],"genre_scores_gemma":[0.9333357,0.001424479,0.06302087,0.00008248526,0.00006279482,0.00006505573,0.0003226815,0.00006232891,0.001623765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001151189,"threshold_uncertainty_score":0.003851056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008217561813519564,"score_gpt":0.3295429562563211,"score_spread":0.3213253944428015,"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."}}