{"id":"W4407441741","doi":"10.1016/j.commatsci.2025.113727","title":"Modulating band gap and optical activity in GaN/Zr<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si143.svg\" display=\"inline\" id=\"d1e1155\"><mml:msub><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math>C<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si117.svg\" display=\"inline\" id=\"d1e1163\"><mml:msub><mml:mrow><mml:mi mathvariant=\"normal\">O</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> Heterostructure via stacking strategies for promising optoelectronic applications","year":2025,"lang":"lv","type":"article","venue":"Computational Materials Science","topic":"MXene and MAX Phase Materials","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"National University of Sciences and Technology","keywords":"Computer science; Materials science","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":[0.0001096376,0.0001202318,0.00008024732,0.0001220062,0.0001342637,0.0004390284,0.000317438,0.0001852591,0.004082794],"category_scores_gemma":[0.0001544495,0.0001139108,0.00008258043,0.0001369633,0.0001934524,0.000240846,0.0001365009,0.0002022411,0.0003918921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004838802,"about_ca_system_score_gemma":0.0001482334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001655745,"about_ca_topic_score_gemma":0.002958437,"domain_scores_codex":[0.9999616,0.000005747508,0.00000138383,0.000008216633,0.000009884373,0.00001309172],"domain_scores_gemma":[0.9999578,0.0000154687,0.0000119896,0.000003260024,0.000005715957,0.000005732301],"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":[0.0004749842,0.0001462515,0.002071276,0.0001554741,0.00002605504,0.0001468079,0.0001899032,0.01183356,0.9263851,0.03882336,0.002862616,0.01688457],"study_design_scores_gemma":[0.00008328132,0.0003448976,0.0080585,0.00003006663,0.0000401757,0.0001294347,0.0002644127,0.1539941,0.8250961,0.005008977,0.006914867,0.00003523375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760073,0.0006213018,0.003035936,0.000240331,0.00002835785,0.000009954066,0.0001900617,0.0001572025,0.01970958],"genre_scores_gemma":[0.9971893,0.0001328324,0.0006664349,0.00001501567,0.000002854956,0.000004299072,0.00005422264,0.00001843788,0.001916559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004082794,"threshold_uncertainty_score":0.01365834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01904622182620668,"score_gpt":0.266935989836059,"score_spread":0.2478897680098524,"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."}}