{"id":"W4399966331","doi":"10.1103/physrevlett.132.266701","title":"Bath-Engineering Magnetic Order in Quantum Spin Chains: An Analytic Mapping Approach","year":2024,"lang":"en","type":"article","venue":"Physical Review Letters","topic":"Quantum many-body systems","field":"Physics and Astronomy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canada Foundation for Innovation; Government of Ontario","keywords":"Ferromagnetism; Spin (aerodynamics); Condensed matter physics; Order (exchange); Quantum; Physics; Heisenberg model; Chain (unit); Spin engineering; Statistical physics; Quantum mechanics; Spin polarization; Electron; Thermodynamics","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"],"consensus_categories":[],"category_scores_codex":[0.0003373748,0.0003124319,0.0005904271,0.0001474134,0.00003213372,0.0001213073,0.000280008,0.00001173149,0.00005823515],"category_scores_gemma":[0.00001395597,0.0002766917,0.000212734,0.0009873024,0.00003414742,0.0002339233,0.00005691828,0.0003855095,0.0002118893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006126958,"about_ca_system_score_gemma":0.00003187486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001137746,"about_ca_topic_score_gemma":4.963047e-7,"domain_scores_codex":[0.9981908,0.0001055007,0.0004254012,0.0005496999,0.0002634447,0.0004651036],"domain_scores_gemma":[0.999302,0.00007164734,0.00005712273,0.0004298326,0.00001789643,0.0001215123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001550388,0.002131322,0.007907495,0.05304866,0.0008427894,0.0002671755,0.005228154,0.03775863,0.08052336,0.711173,0.01145397,0.08964992],"study_design_scores_gemma":[0.0001210704,0.0000294562,0.0009724838,0.00316922,0.00005944547,0.000002119535,0.00005509463,0.9872131,0.00001495843,0.0001567837,0.00783349,0.0003727411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9352044,0.01878572,0.0396289,0.003060197,0.0004575841,0.001340914,0.00001716825,0.0002665127,0.001238562],"genre_scores_gemma":[0.9978235,0.00009725403,0.0002884335,0.0007674167,0.000775572,0.00012206,0.00004013106,0.00005909111,0.00002658705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9494545,"threshold_uncertainty_score":0.9999685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01644860415655183,"score_gpt":0.2743466185695732,"score_spread":0.2578980144130214,"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."}}