{"id":"W7110145864","doi":"10.2139/ssrn.5887964","title":"Sensor Fusion and Control Utilizing Machine Learning in LPBF Additive Manufacturing","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Interpretability; Sensor fusion; Process (computing); Fusion; Pyrometer; Process control; Scalability; Stability (learning theory)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006416423,0.0003609634,0.0006395854,0.0003214123,0.000324928,0.0007721577,0.0005298074,0.0007034739,0.001256103],"category_scores_gemma":[0.001317843,0.0002555129,0.0003290457,0.0005710152,0.0005741809,0.001104304,0.0005693205,0.0009407725,0.0002620224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005505775,"about_ca_system_score_gemma":0.0004429802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002323991,"about_ca_topic_score_gemma":0.001374387,"domain_scores_codex":[0.9995971,0.0001039596,0.00002176517,0.00007874133,0.0001664185,0.00003191907],"domain_scores_gemma":[0.9996641,0.000172916,0.00003671663,0.00003943773,0.00007924503,0.00000759308],"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":[0.0002709012,0.00009996921,0.0004969837,0.0001620811,0.00004287252,0.00007224008,0.00007477394,0.6658351,0.03583213,0.01745854,0.0008465644,0.2788078],"study_design_scores_gemma":[0.000001821773,0.00002929311,0.000154051,0.000003269177,0.000002934734,0.00001026109,0.000003659877,0.9913456,0.004431532,0.003675719,0.0003379493,0.000003990488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02572569,0.0005976069,0.9715188,0.0002208052,0.0000634576,0.0000170694,0.00002482202,0.0002206707,0.001611151],"genre_scores_gemma":[0.8943352,0.0004772341,0.1018963,0.00006962418,0.00006627373,0.00004549947,0.00005606959,0.00003191642,0.00302181],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002323991,"threshold_uncertainty_score":0.00462091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00631373386565435,"score_gpt":0.2176685256568142,"score_spread":0.2113547917911599,"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."}}