{"id":"W1995480307","doi":"10.1021/ed084p1488","title":"Teaching Chromatography Using Virtual Laboratory Exercises","year":2007,"lang":"en","type":"article","venue":"Journal of Chemical Education","topic":"Chromatography in Natural Products","field":"Chemistry","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Virtual Laboratory; Instrumentation (computer programming); Computer science; Robustness (evolution); Software; Chromatographic separation; Chromatography; Elution; Resolution (logic); Chemistry; Multimedia; High-performance liquid chromatography; Artificial intelligence","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":[0.001643752,0.001564218,0.0005866094,0.0007264948,0.0008181385,0.002847536,0.002469635,0.001523786,0.01672783],"category_scores_gemma":[0.007068617,0.0003803627,0.0006820631,0.0003616316,0.0008668119,0.001847764,0.003175488,0.002154093,0.004382378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007481516,"about_ca_system_score_gemma":0.001244421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001862275,"about_ca_topic_score_gemma":0.0004025827,"domain_scores_codex":[0.9988865,0.0003892231,0.00006796927,0.0002391327,0.000247017,0.0001701209],"domain_scores_gemma":[0.9957168,0.001948456,0.0002838681,0.0005019918,0.0003272987,0.001221643],"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":[0.0007590118,0.009903068,0.004730418,0.001146726,0.00006642327,0.001456782,0.006252959,0.02422453,0.04361247,0.0413703,0.09226709,0.7742102],"study_design_scores_gemma":[0.0008980714,0.006370415,0.008882975,0.001389526,0.000136339,0.005309462,0.005075902,0.05947055,0.07300807,0.09500919,0.744087,0.0003624808],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2865185,0.001751453,0.5649096,0.007739747,0.002031782,0.002217359,0.0004944336,0.01118426,0.1231528],"genre_scores_gemma":[0.4448445,0.002561804,0.4929135,0.003017841,0.0006202335,0.002115452,0.0008302333,0.0007221527,0.05237432],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01672783,"threshold_uncertainty_score":0.05596018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008732146758771016,"score_gpt":0.2870209142759743,"score_spread":0.2782887675172033,"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."}}