{"id":"W2617913361","doi":"10.1063/1.4983612","title":"Advanced materials for magnetic cooling: Fundamentals and practical aspects","year":2017,"lang":"en","type":"article","venue":"Applied Physics Reviews","topic":"Magnetic and transport properties of perovskites and related materials","field":"Materials Science","cited_by":290,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Regroupement Québécois sur les Matériaux de Pointe; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Canada Foundation for Innovation","keywords":"Magnetic refrigeration; Refrigerant; Adiabatic process; Materials science; Intermetallic; Thermodynamics; Metallurgy; Magnetic field; Heat exchanger; Physics; Magnetization","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006487659,0.0002556268,0.0006331562,0.00001132469,0.0005683749,0.0004477077,0.0002167031,0.00009024736,0.0009980776],"category_scores_gemma":[0.00006029812,0.0001842338,0.00006902249,0.00001745468,0.0002470714,0.0002122842,0.00010522,0.0000629079,0.0002688213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001390196,"about_ca_system_score_gemma":0.0000358388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002064268,"about_ca_topic_score_gemma":0.000002362607,"domain_scores_codex":[0.9985082,0.00002972375,0.0004935054,0.0004433237,0.0001703782,0.0003548856],"domain_scores_gemma":[0.9987774,0.0000487224,0.0004113074,0.0005906282,0.00005477467,0.0001171303],"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":[0.0001458456,0.00006174837,0.000002448659,0.0004281504,0.000006972407,0.000002659102,0.00006724773,0.000001604595,0.9485404,0.02981004,0.0005829998,0.02034988],"study_design_scores_gemma":[0.001424807,0.0002518807,0.000168825,0.0001890325,0.0001763032,0.00001161884,0.00003431057,0.00001014543,0.7225685,0.0103478,0.2643485,0.0004683539],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542782,0.01050303,0.002271501,0.0007529748,0.001782428,0.005617724,0.0002178935,0.0001396321,0.02443657],"genre_scores_gemma":[0.9806017,0.00637916,0.01116001,0.0003214045,0.0003809918,0.0005345615,0.00003148509,0.00004149868,0.0005491513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2637655,"threshold_uncertainty_score":0.9999151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04225070227845731,"score_gpt":0.306225979207888,"score_spread":0.2639752769294307,"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."}}