{"id":"W4417150889","doi":"10.3390/mi16121392","title":"Predicting Liquid Crystal Behavior with Artificial Neural Networks","year":2025,"lang":"en","type":"article","venue":"Micromachines","topic":"Liquid Crystal Research Advancements","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Refractive index; Liquid crystal; Polar; Anchoring; Orientation (vector space); Viscosity","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":[],"consensus_categories":[],"category_scores_codex":[0.0002796245,0.0002070851,0.0002059771,0.0001051127,0.0003121339,0.0001885266,0.0003840407,0.00005632704,0.0002327581],"category_scores_gemma":[0.00009034501,0.0001593181,0.00004734025,0.0003033328,0.0001749816,0.0003198607,0.0002842255,0.0002007058,0.00001916587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006879088,"about_ca_system_score_gemma":0.00006897646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001732253,"about_ca_topic_score_gemma":0.0002142063,"domain_scores_codex":[0.998302,0.0000929572,0.0002981693,0.0004227069,0.0003043358,0.000579875],"domain_scores_gemma":[0.9993114,0.00007843474,0.00007903199,0.0003224525,0.0001033042,0.0001053728],"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":[0.0006265153,0.0001194389,0.01345985,0.00002353453,0.00001020302,0.0000494682,0.00005004929,0.001234813,0.983103,0.0001092127,0.000154589,0.001059285],"study_design_scores_gemma":[0.002149296,0.002248612,0.01793942,0.0002856142,0.0001589576,0.0001072171,0.0003369684,0.03182296,0.9410661,0.0002964067,0.002601832,0.0009866048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934481,0.0002244527,0.004508188,0.0001809179,0.0004704764,0.0004144743,0.00003458478,0.000182155,0.0005366246],"genre_scores_gemma":[0.9980003,0.000003162307,0.0008664132,0.0001507523,0.0001777623,0.000108558,0.00002169139,0.00002349669,0.0006478599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04203692,"threshold_uncertainty_score":0.6496803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0129745316608457,"score_gpt":0.2928932954485216,"score_spread":0.2799187637876759,"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."}}