{"id":"W4386644448","doi":"10.48550/arxiv.2309.04648","title":"Discovery of Charge Order in the Transition Metal Dichalcogenide Fe$_{x}$NbS$_2$","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"2D Materials and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"SLAC National Accelerator Laboratory; Brookhaven National Laboratory; Argonne National Laboratory; Basic Energy Sciences; Canadian Institute for Advanced Research; U.S. Department of Energy; Division of Materials Research; Office of Science; Research Corporation for Science Advancement; National Science Foundation","keywords":"Charge ordering; Zigzag; Charge (physics); Materials science; Condensed matter physics; Antiferromagnetism; Transition metal; Phase (matter); Synchrotron; Metal; Order (exchange); Phase transition; Crystallography; Chemistry; Physics; Optics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004257932,0.0001214638,0.0001322792,0.0001749574,0.0002116445,0.0002563376,0.0001609069,0.0001754368,0.0006047316],"category_scores_gemma":[0.0001201067,0.0001648129,0.00005890926,0.0001223391,0.0003149979,0.0001789087,0.000162199,0.000179215,0.00009322617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002588338,"about_ca_system_score_gemma":0.0001536254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001351557,"about_ca_topic_score_gemma":0.002845023,"domain_scores_codex":[0.9999486,0.000005130324,0.000003047698,0.00001267348,0.00001958748,0.00001090681],"domain_scores_gemma":[0.9999567,0.000007113182,0.00001038374,0.000005512673,0.00001276197,0.000007491896],"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":[0.0000421943,0.000005374276,0.0007815373,0.00001876873,0.000002200371,0.00004901299,0.00002590228,0.00009389772,0.9979694,0.0002665308,0.00004154259,0.0007036217],"study_design_scores_gemma":[0.00000873757,0.00004653369,0.005959389,0.000003016883,0.000004656528,0.0001778088,0.00005640799,0.00214678,0.9903351,0.0001339002,0.001122315,0.000005416503],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983534,0.00008896769,0.0004743267,0.00003362209,0.000004659627,0.000002524298,0.00006838801,0.00002301713,0.0009511833],"genre_scores_gemma":[0.9985645,0.00005120915,0.0007746039,0.00001099875,0.000001639218,0.000003826074,0.00008106557,0.000006992592,0.0005052388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001351557,"threshold_uncertainty_score":0.002687335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09216922378871503,"score_gpt":0.2078014644534992,"score_spread":0.1156322406647842,"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."}}