{"id":"W4251419967","doi":"10.1002/cjce.23551","title":"Issue Highlights","year":2020,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Industrial Gas Emission Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Computer science; Library science; Information retrieval","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":[0.0001026006,0.0001123022,0.0001797586,0.00005247826,0.00002769395,0.00004306979,0.0003299243,0.00008881248,0.0001743123],"category_scores_gemma":[0.0002442762,0.00008331711,0.00007760338,0.0001591469,0.00001943908,0.00006590468,0.000005994019,0.000489322,0.00003260774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205536,"about_ca_system_score_gemma":0.0001391468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006854488,"about_ca_topic_score_gemma":0.000008773136,"domain_scores_codex":[0.9993083,0.00000597407,0.0002582528,0.00004737772,0.0001309112,0.0002492065],"domain_scores_gemma":[0.9990413,0.00005251161,0.00003077321,0.00008542226,0.00004985024,0.0007402024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001913086,0.000002564653,0.0000200761,0.00006485886,0.0001895663,0.0002421231,0.001262846,0.4137093,0.5003475,0.001323516,0.0794187,0.003399859],"study_design_scores_gemma":[0.0006936522,0.00003168672,0.00001052982,0.00008473752,0.00004860684,0.000125986,0.00001258094,0.1158624,0.4187702,0.00004401948,0.4640335,0.0002821495],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8620159,0.006293145,0.009260165,0.1027372,0.008908185,0.0006455304,0.00003713163,0.0006211358,0.009481578],"genre_scores_gemma":[0.9977769,0.000001739145,0.0002506404,0.0002683434,0.001653384,8.022203e-7,4.000019e-7,0.00002872916,0.00001904353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3846148,"threshold_uncertainty_score":0.3397573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076371366413638,"score_gpt":0.173531973528218,"score_spread":0.1627682598640816,"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."}}