{"id":"W4406863765","doi":"10.3390/ma18030568","title":"Effect of Porosity on Tribological Properties of Medical-Grade 316L Stainless Steel Manufactured by Laser-Based Powder Bed Fusion","year":2025,"lang":"en","type":"article","venue":"Materials","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Alberta","funders":"Agencia Nacional de Investigación y Desarrollo; Universidad de las Fuerzas Armadas ESPE; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación","keywords":"Materials science; Porosity; Microstructure; Tribology; Abrasion (mechanical); Context (archaeology); Scanning electron microscope; Fusion; Composite material; Silicon nitride; Laser power scaling; Laser; Layer (electronics); Optics","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":[0.0003540463,0.0001942013,0.0001485926,0.0003716011,0.0001038869,0.000208055,0.0001559116,0.000271867,0.0006025847],"category_scores_gemma":[0.001019243,0.0002057308,0.0001684787,0.0002139071,0.0003251614,0.0002371213,0.0001518679,0.0001824896,0.00009799712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000161576,"about_ca_system_score_gemma":0.0001142402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003190193,"about_ca_topic_score_gemma":0.00074094,"domain_scores_codex":[0.9997255,0.00004366943,0.00003053686,0.00004583497,0.0001066575,0.00004783733],"domain_scores_gemma":[0.9991872,0.0003600471,0.0002572852,0.00005765582,0.00009543988,0.00004237293],"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":[0.0002459814,0.00001301683,0.001182337,0.0000597582,0.000007355233,0.00007398037,0.00005489,0.0007610503,0.994934,0.000042364,0.0000134234,0.002611747],"study_design_scores_gemma":[0.000006592601,0.0003771287,0.01320045,0.000008764634,0.00002199836,0.000132779,0.0000572093,0.00137608,0.984473,0.00001855905,0.000316666,0.0000107407],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987547,0.0003052545,0.0006719349,0.000006908054,0.000003432736,0.000003412964,0.0000406841,0.0000169795,0.0001966301],"genre_scores_gemma":[0.9994117,0.00007756201,0.0003940116,0.000002762794,0.000001054131,0.00000202722,0.00001989535,0.00000512889,0.00008588828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006025847,"threshold_uncertainty_score":0.002015829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009080578364524038,"score_gpt":0.2370952208042725,"score_spread":0.2280146424397485,"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."}}