{"id":"W7117357404","doi":"10.1016/j.jprocont.2025.103614","title":"Robust soft sensing with causal and injectivity-preserving Graph Neural Network","year":2025,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Advanced Graph Neural Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Centre for Clean Coal/Carbon and Mineral Processing Technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Graph; A priori and a posteriori; Benchmark (surveying); Artificial neural network; Noise (video); Graph theory; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008056463,0.00109404,0.0006127572,0.0004522561,0.0003068012,0.0006812532,0.001126798,0.001045459,0.0007900752],"category_scores_gemma":[0.003242244,0.0004320621,0.0005438256,0.0003796509,0.0009967578,0.001594202,0.001286976,0.001398071,0.0001668237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009062747,"about_ca_system_score_gemma":0.0008210443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005460008,"about_ca_topic_score_gemma":0.006540879,"domain_scores_codex":[0.9996694,0.00009525639,0.00001447781,0.0001014924,0.00008423961,0.0000351772],"domain_scores_gemma":[0.9990489,0.0005337778,0.0001422191,0.0001075583,0.0001288948,0.0000387044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004453806,0.00002227429,0.0003557903,0.00002958218,0.00001920167,0.00003643744,0.00003115402,0.9637257,0.002171948,0.006149777,0.0002703191,0.02714324],"study_design_scores_gemma":[0.000001345044,0.000006242167,0.00002490629,0.000001245002,0.000001230154,0.00000294637,0.000001541911,0.9976636,0.000313632,0.001944796,0.00003696727,0.000001522519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02346974,0.0001203245,0.9750208,0.0001545774,0.00002014872,0.00002034886,0.00004074115,0.0003256895,0.0008276207],"genre_scores_gemma":[0.8770607,0.0001553044,0.1202633,0.0001677369,0.00003066377,0.00007293464,0.0001499256,0.00007126215,0.002028213],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005460008,"threshold_uncertainty_score":0.01085645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009426928147155785,"score_gpt":0.236227339357869,"score_spread":0.2268004112107132,"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."}}