{"id":"W4292458044","doi":"10.21203/rs.3.rs-1848053/v1","title":"Data-driven texture design for nearly-isotropic elastic and plastic properties in titanium-based materials","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Isotropy; Texture (cosmology); Materials science; Titanium; Composite material; Metallurgy; Computer science; Optics; Artificial intelligence; Physics; Image (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":[0.0004318896,0.0004170734,0.0005013898,0.0004073872,0.0001485677,0.0006351053,0.0008125029,0.000566466,0.001738273],"category_scores_gemma":[0.001322343,0.0002987165,0.0004504884,0.0003119254,0.0003508359,0.0005375612,0.0004721642,0.0006278888,0.0003490093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004240735,"about_ca_system_score_gemma":0.000533691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001152288,"about_ca_topic_score_gemma":0.001999779,"domain_scores_codex":[0.9998671,0.00001866006,0.000006567911,0.00002764651,0.0000600044,0.00002003362],"domain_scores_gemma":[0.9995628,0.0001868744,0.00004717612,0.00004035734,0.00014071,0.00002203837],"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":[0.0002088325,0.0001222752,0.0009107706,0.0002158266,0.00002706253,0.00004673181,0.00003993469,0.7954925,0.05205866,0.006276049,0.001460897,0.1431404],"study_design_scores_gemma":[0.000005284277,0.0000136903,0.00005747613,0.000001700058,0.000001976288,0.000004240153,0.000003526421,0.9963915,0.002394348,0.0008711678,0.000253314,0.000001827192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06246698,0.000272463,0.9339179,0.0001721644,0.00005413251,0.00003614618,0.0001555303,0.0005459011,0.002378705],"genre_scores_gemma":[0.7947916,0.0001998281,0.2022249,0.0000925754,0.00003130449,0.000107279,0.0003470702,0.0002534732,0.001951869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001738273,"threshold_uncertainty_score":0.005815148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.152466777322228,"score_gpt":0.3930507807946264,"score_spread":0.2405840034723984,"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."}}