{"id":"W4379162853","doi":"10.1002/cjce.24455","title":"Issue Highlights","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Gerontology; Computer science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001331898,0.00006617406,0.00008461553,0.0001012965,0.00003218393,0.00003574417,0.0001405438,0.00003913663,0.00004697673],"category_scores_gemma":[0.00007680994,0.00005166473,0.00003768169,0.0002614934,0.00001502836,0.00007660899,0.000002291804,0.0001775215,0.00007808238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009481281,"about_ca_system_score_gemma":0.00007099169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004737909,"about_ca_topic_score_gemma":0.00005703199,"domain_scores_codex":[0.9995025,0.000003850259,0.0001688476,0.00002928203,0.00009589996,0.0001996045],"domain_scores_gemma":[0.9996307,0.00005322814,0.00001876239,0.00006594532,0.00003780481,0.000193559],"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":[0.000003726166,0.000001827483,0.00002440325,0.00005265969,0.00009119257,0.0000577123,0.002266545,0.443918,0.4721117,0.004324374,0.07521134,0.001936592],"study_design_scores_gemma":[0.0004764099,0.00003921108,0.0005321056,0.0001076791,0.00004005263,0.0001885445,0.00005330267,0.3323564,0.5768026,0.001057711,0.08795469,0.0003913724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882576,0.0003956789,0.003624392,0.00413795,0.001827335,0.00009333293,0.000006423146,0.0002389209,0.001418364],"genre_scores_gemma":[0.999411,0.000006022664,0.0002108323,0.00004498832,0.0002409223,0.000001432465,0.000003152076,0.00001720392,0.0000644558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1115616,"threshold_uncertainty_score":0.2106826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007048299184148146,"score_gpt":0.1878268098478336,"score_spread":0.1807785106636855,"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."}}