{"id":"W4415659058","doi":"10.1063/5.0288278","title":"Abinit 2025: New capabilities for the predictive modeling of solids and nanomaterials","year":2025,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Nonlocal and gradient elasticity in micro/nano structures","field":"Materials Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Trinity College; Université de Montréal; Université du Québec à Montréal; Université du Québec à Trois-Rivières","funders":"Fonds De La Recherche Scientifique - FNRS; HORIZON EUROPE Marie Sklodowska-Curie Actions; HORIZON EUROPE Framework Programme; Fonds Wetenschappelijk Onderzoek; Trinity College Dublin; Waalse Gewest; HORIZON EUROPE European Research Council; Simons Foundation","keywords":"Workflow; Context (archaeology); Software; Field (mathematics); Computation; Excited state","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001449904,0.001440684,0.001441615,0.000994794,0.0008614422,0.001670304,0.003673231,0.001578564,0.01756175],"category_scores_gemma":[0.002429698,0.0006929084,0.001843554,0.001184823,0.0005569962,0.001745268,0.002051438,0.002013043,0.003959127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076347,"about_ca_system_score_gemma":0.001795495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008471085,"about_ca_topic_score_gemma":0.008628905,"domain_scores_codex":[0.9994081,0.0001309387,0.00003758984,0.00004843027,0.0003288566,0.00004604593],"domain_scores_gemma":[0.9993247,0.0003252639,0.00003963969,0.0001055831,0.0001461459,0.00005867805],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006171004,0.0003114054,0.004049878,0.002174527,0.0007739207,0.0006588179,0.0004740511,0.5750537,0.01297633,0.1685208,0.1244656,0.109924],"study_design_scores_gemma":[0.0000846913,0.00004275258,0.0003360547,0.0001004203,0.00003804891,0.00009378416,0.00002333043,0.9008306,0.002750332,0.02533394,0.07032011,0.00004606813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02940623,0.003008237,0.8264527,0.001310352,0.0008643386,0.0003115687,0.01777079,0.07143649,0.0494393],"genre_scores_gemma":[0.2645638,0.003377421,0.6567819,0.001196851,0.0003707191,0.002191087,0.03572159,0.02023106,0.01556576],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01756175,"threshold_uncertainty_score":0.05874997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535494954988009,"score_gpt":0.2557316171501253,"score_spread":0.2403766676002452,"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."}}