{"id":"W4246466458","doi":"10.15278/isms.2021.fh03","title":"USING COMPUTATIONAL TOOLS TO ENHANCE LEARNING IN AN UNDERGRADUATE MOLECULAR SPECTROSCOPY COURSE","year":2021,"lang":"en","type":"article","venue":"Proceedings of the 2021 International Symposium on Molecular Spectroscopy","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Complement (music); Class (philosophy); Focus (optics); Plan (archaeology); Computer science; Component (thermodynamics); Spectroscopy; Undergraduate research; Molecular spectroscopy; Electron spectroscopy; Mathematics education; Chemistry; Physics; Artificial intelligence; Psychology; Quantum mechanics; Optics; Medical education","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":[0.00473523,0.001406297,0.0007584676,0.001003277,0.001007635,0.004551499,0.003332717,0.00148714,0.01498678],"category_scores_gemma":[0.01814132,0.0006980571,0.0009525397,0.001076736,0.0006800454,0.004180802,0.004582345,0.00305149,0.004568642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001518082,"about_ca_system_score_gemma":0.002077268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001144104,"about_ca_topic_score_gemma":0.001993214,"domain_scores_codex":[0.9981615,0.0008713282,0.00009619154,0.0002712399,0.000421859,0.0001779912],"domain_scores_gemma":[0.9913174,0.00563756,0.0002876407,0.0009325694,0.001005129,0.0008198006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001095533,0.004274785,0.01050469,0.0007962051,0.0001406762,0.0005531404,0.002636409,0.1682681,0.0112549,0.08560739,0.09178397,0.6230842],"study_design_scores_gemma":[0.0006831829,0.0007182808,0.002513924,0.0003762151,0.000101049,0.000190455,0.001591726,0.701456,0.02630679,0.1291687,0.1367006,0.0001932361],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2339769,0.0004502261,0.649514,0.0113924,0.0009604443,0.0008759983,0.001646445,0.02169568,0.07948793],"genre_scores_gemma":[0.2302887,0.0003452698,0.754065,0.0008734235,0.00008297087,0.001099863,0.001895821,0.001439647,0.009909274],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01498678,"threshold_uncertainty_score":0.05013579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352993232144766,"score_gpt":0.3295377630754365,"score_spread":0.3160078307539889,"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."}}