{"id":"W4412040663","doi":"10.1002/cjce.25333","title":"Issue Highlights","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001749703,0.00006454337,0.00009773162,0.0001046718,0.00004619442,0.000107436,0.0008019694,0.00004239929,0.000007128735],"category_scores_gemma":[0.00007720027,0.00004553374,0.00004660079,0.000233356,0.00002241747,0.0001030349,0.00002161642,0.0002361143,0.000007273555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007956097,"about_ca_system_score_gemma":0.0004224108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002936836,"about_ca_topic_score_gemma":0.00003598382,"domain_scores_codex":[0.9995019,0.000007142222,0.0001660155,0.00006102987,0.00008633263,0.0001776169],"domain_scores_gemma":[0.9994698,0.00005070231,0.00003343644,0.0001700157,0.00008143525,0.000194673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000401956,0.00001114913,0.00003954813,0.00004504816,0.0001089227,0.0001223417,0.0009190022,0.02547273,0.05545485,0.8827478,0.01659907,0.01847546],"study_design_scores_gemma":[0.0005269831,0.0000478186,0.0001473743,0.0005539307,0.00004341542,0.0003070945,0.000009002043,0.4726105,0.3869067,0.02879282,0.1095941,0.0004603184],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03954082,0.001245217,0.9293704,0.02583356,0.001620704,0.00004680307,7.574554e-7,0.00004329217,0.002298427],"genre_scores_gemma":[0.9941421,0.000001570375,0.005281151,0.000346762,0.0001057474,4.885848e-7,7.001861e-8,0.00000298528,0.0001191038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9546013,"threshold_uncertainty_score":0.1856812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00801863749773018,"score_gpt":0.2032998560205714,"score_spread":0.1952812185228412,"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."}}