{"id":"W4406902688","doi":"10.1038/s44286-025-00172-3","title":"Exploring the potential landscape of chemical engineering science","year":2025,"lang":"en","type":"article","venue":"Nature Chemical Engineering","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Science and engineering; Engineering ethics; Engineering; Data science; Computer science","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":[0.0002250269,0.000248688,0.0002457042,0.0002881754,0.00003229341,0.00003979638,0.0005821041,0.0002185929,0.00001142549],"category_scores_gemma":[0.0003269536,0.0002046969,0.0001015133,0.001467902,0.00009502924,0.0002174961,0.0001142652,0.001034631,0.000004012183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205563,"about_ca_system_score_gemma":0.00004536227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001463898,"about_ca_topic_score_gemma":1.457694e-8,"domain_scores_codex":[0.9985936,0.000002289486,0.0003120766,0.0002595877,0.0003640694,0.0004684377],"domain_scores_gemma":[0.9993188,0.0001080585,0.00001888602,0.0003459659,0.00007575314,0.0001324964],"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":[0.000003882152,0.0000161219,0.00001213409,0.0004736652,0.00003979087,0.000001517619,0.00005627606,0.05192411,0.9434073,0.001476842,0.0003752836,0.002213066],"study_design_scores_gemma":[0.000178095,0.000003609894,0.0005981683,0.0001969796,0.00002481185,0.000008962777,0.00001199123,0.2672154,0.7302393,0.00002512416,0.001283951,0.0002136927],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822288,0.001486119,0.01151262,0.0002789331,0.003214539,0.0001361915,0.000005822842,0.0006838146,0.0004531715],"genre_scores_gemma":[0.9968647,0.00003361966,0.002647613,0.00002618433,0.0003265006,0.00004716769,0.000008600005,0.0000349806,0.00001061561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2152912,"threshold_uncertainty_score":0.8347296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005235114367030317,"score_gpt":0.193939382835329,"score_spread":0.1887042684682987,"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."}}