{"id":"W2588422802","doi":"10.1021/acs.inorgchem.6b02912","title":"Synthetic Approach for (Mn,Fe)<sub>2</sub>(Si,P) Magnetocaloric Materials: Purity, Structural, Magnetic, and Magnetocaloric Properties","year":2017,"lang":"en","type":"article","venue":"Inorganic Chemistry","topic":"Magnetic and transport properties of perovskites and related materials","field":"Materials Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Magnetic refrigeration; Chemistry; Curie temperature; Magnetization; Annealing (glass); Synchrotron; Diffraction; Magnetic hysteresis; Condensed matter physics; Crystallography; Analytical Chemistry (journal); Thermodynamics; Metallurgy; Ferromagnetism; Materials science; Magnetic field; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005188153,0.0006057956,0.0007405735,0.00003895075,0.001105194,0.001106529,0.001015451,0.0004644719,0.001415814],"category_scores_gemma":[0.0002151321,0.0004682803,0.0001215948,0.00005799721,0.0008450306,0.0003753546,0.0004003352,0.0002115373,0.00006552844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006925058,"about_ca_system_score_gemma":0.0001357509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001550676,"about_ca_topic_score_gemma":0.000005072628,"domain_scores_codex":[0.9967917,0.00004263722,0.0007855416,0.001062669,0.0004737379,0.000843779],"domain_scores_gemma":[0.9978328,0.00003671467,0.0004005779,0.00120965,0.0002280406,0.0002922599],"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":[0.0002306261,0.00007336095,0.00003294383,0.001683976,0.00002182418,0.00001489543,0.0001178793,0.00000302152,0.9952339,0.0000663005,0.0004360984,0.002085186],"study_design_scores_gemma":[0.001231077,0.0002376901,0.0003936429,0.0001128355,0.0002016336,0.0001689788,0.0001195221,0.0001866773,0.9950283,0.0003302934,0.001272096,0.0007172307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923784,0.003540458,0.0001030369,0.0002793262,0.0008122894,0.0009421391,0.0002531785,0.0001895939,0.001501538],"genre_scores_gemma":[0.9958023,0.0006665097,0.00111659,0.00006685086,0.0006095574,0.000265078,0.00007255738,0.00009713669,0.001303463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003423817,"threshold_uncertainty_score":0.9999304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314153375645847,"score_gpt":0.2011040461195102,"score_spread":0.1879625123630517,"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."}}