{"id":"W4366988527","doi":"10.3390/mi14050925","title":"SiCNFe Ceramics as Soft Magnetic Material for MEMS Magnetic Devices: A Mössbauer Study","year":2023,"lang":"en","type":"article","venue":"Micromachines","topic":"Advanced ceramic materials synthesis","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Materials science; Ceramic; Paramagnetism; Microfabrication; Microelectromechanical systems; Nanoparticle; Magnetic nanoparticles; Chemical engineering; Magnet; Ferromagnetism; Analytical Chemistry (journal); Nanotechnology; Composite material; Condensed matter physics; Chemistry; Mechanical engineering; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007280668,0.0005328277,0.0006664117,0.0002236754,0.0003804265,0.0004329811,0.0007808584,0.0001459601,0.004118694],"category_scores_gemma":[0.0002677312,0.0004711867,0.0001354785,0.0003636877,0.0001522019,0.0002669663,0.0003561818,0.00008663656,0.002312982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007571188,"about_ca_system_score_gemma":0.00008220436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004686242,"about_ca_topic_score_gemma":0.0002018102,"domain_scores_codex":[0.9968002,0.0001877776,0.0007471943,0.0009463815,0.0003836682,0.0009348227],"domain_scores_gemma":[0.99839,0.0003654683,0.000214991,0.0007500813,0.0001267461,0.0001527358],"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":[0.0002502309,0.0002159667,0.0007137728,0.0001512793,0.00001486762,0.00003794198,0.0009126588,0.00008508219,0.9921381,0.000133137,0.0008578209,0.00448909],"study_design_scores_gemma":[0.005164106,0.003397585,0.01705277,0.0001681371,0.0004743162,0.0001768045,0.002309227,0.002003507,0.9232966,0.01421435,0.02914541,0.002597207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930755,0.0001611387,0.0002215591,0.0002327724,0.002693623,0.001826888,0.0006057164,0.0008711084,0.00031169],"genre_scores_gemma":[0.991562,0.00001908012,0.003600687,0.0003050421,0.0007134562,0.0006429022,0.000124495,0.0001714021,0.002860913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06884158,"threshold_uncertainty_score":0.999774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384858949547303,"score_gpt":0.2755087596448297,"score_spread":0.2616601701493567,"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."}}