{"id":"W4224237874","doi":"10.1038/s42005-022-00853-y","title":"Tutorial: a beginner’s guide to interpreting magnetic susceptibility data with the Curie-Weiss law","year":2022,"lang":"en","type":"article","venue":"Communications Physics","topic":"Advanced Condensed Matter Physics","field":"Physics and Astronomy","cited_by":501,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canada First Research Excellence Fund; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Magnetic susceptibility; Magnetism; Interpretation (philosophy); Paramagnetism; Condensed matter physics; Characterization (materials science); Curie; Curie–Weiss law; Physics; Theoretical physics; Curie temperature; Computer science; Materials science; Nanotechnology; Ferromagnetism","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001411324,0.002221053,0.001817997,0.003078225,0.0007592566,0.001972419,0.002402547,0.001846997,0.09580205],"category_scores_gemma":[0.006309741,0.001135916,0.001297308,0.002228316,0.0008936509,0.003836514,0.001615155,0.00442932,0.08027049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000923273,"about_ca_system_score_gemma":0.001462403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001679966,"about_ca_topic_score_gemma":0.003179,"domain_scores_codex":[0.9993485,0.0001463939,0.00005443849,0.00009771493,0.0003139047,0.0000390274],"domain_scores_gemma":[0.9968163,0.001446479,0.0001528875,0.0001710042,0.001134973,0.0002783005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003018789,0.00005651545,0.0001132241,0.0009359132,0.00001610752,0.0001812621,0.0001360648,0.000599494,0.002887137,0.01200146,0.8950974,0.08794538],"study_design_scores_gemma":[0.000007957849,0.00002423571,0.0002637354,0.0002523153,0.000004983558,0.0003839969,0.0000316403,0.0005072686,0.0004302209,0.01276578,0.9853055,0.00002248204],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002884344,0.203893,0.4734815,0.03994315,0.02985975,0.001322378,0.02122227,0.02969648,0.197697],"genre_scores_gemma":[0.01125323,0.1662878,0.3780304,0.02831042,0.0221,0.002182484,0.01482107,0.01287528,0.3641393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09580205,"threshold_uncertainty_score":0.3204898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02955497291314308,"score_gpt":0.3218681482264786,"score_spread":0.2923131753133356,"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."}}