{"id":"W4416600516","doi":"10.1149/ma2025-02341702mtgabs","title":"<i>(Invited)</i> Computational Insights into Polycrystalline Materials Used for Fuel Cells and Batteries","year":2025,"lang":"","type":"article","venue":"ECS Meeting Abstracts","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Crystallite; Grain boundary; Fuel cells; Work (physics); Dopant; Amorphous solid; Computational model; Context (archaeology); Granularity","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003676439,0.0008079657,0.001073778,0.0004273884,0.001243191,0.00235805,0.0009285925,0.0003941384,0.0002315749],"category_scores_gemma":[0.001631801,0.0008158806,0.0001126161,0.0004783895,0.0009723526,0.0007237973,0.0006696227,0.000285945,0.00009221962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001439128,"about_ca_system_score_gemma":0.0002808914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008253732,"about_ca_topic_score_gemma":0.00008453905,"domain_scores_codex":[0.9938525,0.0005870726,0.002060518,0.001628495,0.0007808142,0.001090631],"domain_scores_gemma":[0.9951489,0.002234909,0.001265439,0.0006261829,0.0004077534,0.0003168128],"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":[0.0002084197,0.0001359515,0.0001428567,0.002455153,0.00003122696,0.0000142532,0.002489234,0.1041707,0.888296,0.00008717825,0.001913145,0.00005588885],"study_design_scores_gemma":[0.001531229,0.0002279854,0.002848172,0.001349546,0.0001191232,0.00001181589,0.000304456,0.009012732,0.9531636,0.01064446,0.01992713,0.0008598149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816811,0.0009927931,0.001528872,0.006138636,0.006758166,0.001243603,0.0002473965,0.0002301385,0.001179314],"genre_scores_gemma":[0.9489808,0.0001096615,0.04735348,0.002330806,0.0005278511,0.00008367986,0.00009241663,0.00007440923,0.0004468731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09515796,"threshold_uncertainty_score":0.9994292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102904739665326,"score_gpt":0.2637620740418908,"score_spread":0.2534716000753582,"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."}}