{"id":"W2966449564","doi":"10.3390/nano9081119","title":"Composition―Nanostructure Steered Performance Predictions in Steel Wires","year":2019,"lang":"en","type":"article","venue":"Nanomaterials","topic":"Hydrogen embrittlement and corrosion behaviors in metals","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi; Università degli Studi di Roma Tor Vergata; Magyar Tudományos Akadémia","keywords":"Materials science; Austenite; Martensite; Metallurgy; Nanostructure; Corrosion; Metastability; Neutron diffraction; Scanning electron microscope; Pitting corrosion; Microstructure; Diffraction; Composite material; Nanotechnology","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":[0.0001220878,0.0002625731,0.0001503807,0.0002128823,0.0001015856,0.0002267091,0.0002753048,0.0003532018,0.000605059],"category_scores_gemma":[0.000291636,0.0001912006,0.0001259935,0.0001062456,0.0001093769,0.000176083,0.0001097421,0.00008284261,0.0003514036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005073417,"about_ca_system_score_gemma":0.0001795299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00140568,"about_ca_topic_score_gemma":0.001996869,"domain_scores_codex":[0.9999366,0.000005423777,0.000001641962,0.00001842109,0.00003178477,0.000006102275],"domain_scores_gemma":[0.9999506,0.00001340595,0.00001130708,0.000005836808,0.00001608267,0.000002681337],"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":[0.0001191656,0.0000311921,0.002720274,0.00007176732,0.00001364575,0.0001809833,0.00003381962,0.3404101,0.641722,0.001690714,0.0002886497,0.01271782],"study_design_scores_gemma":[0.000005296931,0.00006928265,0.002166329,0.000003164904,0.000004639865,0.0000336432,0.00001209763,0.890635,0.1057444,0.0004347802,0.0008848233,0.000006596376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312302,0.0004046259,0.05906093,0.00006778804,0.00002065424,0.00002485416,0.0002238381,0.0004245607,0.008542575],"genre_scores_gemma":[0.9918805,0.0001107575,0.006701657,0.00000581885,0.000002108638,0.000008162964,0.0000748794,0.00003198238,0.001184159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00140568,"threshold_uncertainty_score":0.003681004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008812644483491726,"score_gpt":0.2306014756855732,"score_spread":0.2217888312020815,"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."}}