{"id":"W2962430200","doi":"10.1016/b978-0-12-813856-4.00004-1","title":"Phase-field modeling for elastic domain engineering applications","year":2019,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Ferroelectric and Piezoelectric Materials","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Ferroelectricity; Materials science; Field (mathematics); Domain (mathematical analysis); Nanocomposite; Phase (matter); Stability (learning theory); Engineering physics; Nanotechnology; Mechanical engineering; Engineering; Computer science; Optoelectronics; Physics; Mathematics","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":[0.0001268267,0.0006705406,0.0004230539,0.000305776,0.0002173452,0.0007182847,0.0009539307,0.0008977528,0.01755203],"category_scores_gemma":[0.0002752786,0.0003129092,0.0004169176,0.0005076777,0.000227482,0.001005929,0.000450039,0.0007202317,0.00486596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002628995,"about_ca_system_score_gemma":0.0002989926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001407589,"about_ca_topic_score_gemma":0.001488337,"domain_scores_codex":[0.9999459,0.000009429733,0.000002137351,0.000008607744,0.00002981043,0.000004191912],"domain_scores_gemma":[0.9999379,0.00002201391,0.00000452358,0.00001248757,0.00001972114,0.000003351095],"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":[0.00003483034,0.00008410397,0.0002063557,0.0003441029,0.00003102706,0.0001332479,0.00007249926,0.5291771,0.02358336,0.1838767,0.03023718,0.2322196],"study_design_scores_gemma":[0.000005604875,0.00001006422,0.0000751259,0.0000314728,0.000005617675,0.00005375958,0.00001341965,0.9112309,0.002764864,0.03373604,0.05206655,0.00000670794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003195054,0.001345296,0.9360606,0.0003315842,0.0002301035,0.00003396665,0.0003376182,0.001122736,0.05734304],"genre_scores_gemma":[0.1875503,0.007007843,0.5513713,0.0003870733,0.000342865,0.0003360609,0.0018077,0.001594667,0.2496023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01755203,"threshold_uncertainty_score":0.05871737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01577653379733471,"score_gpt":0.2484319959053584,"score_spread":0.2326554621080237,"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."}}