{"id":"W2158179267","doi":"10.1002/adem.201200246","title":"Multiple Memory Shape Memory Alloys","year":2013,"lang":"en","type":"article","venue":"Advanced Engineering Materials","topic":"Shape Memory Alloy Transformations","field":"Materials Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Smarter Alloys (Canada)","funders":"","keywords":"Shape-memory alloy; Materials science; Nickel titanium; SMA*; Embedding; Fabrication; Transformation (genetics); Component (thermodynamics); Set (abstract data type); Computer science; Nanotechnology; Artificial intelligence; Metallurgy; Algorithm; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003243856,0.0003453869,0.000401226,0.0001318483,0.0001281627,0.0001993717,0.0004510897,0.0001126543,0.009815317],"category_scores_gemma":[0.0002271661,0.0003388633,0.00006914576,0.0001625584,0.00005284806,0.001385867,0.00008511092,0.0001023186,0.004700665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007718507,"about_ca_system_score_gemma":0.00002654491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005991801,"about_ca_topic_score_gemma":0.000003092144,"domain_scores_codex":[0.9980332,0.00004882032,0.0005865141,0.0003985959,0.000291258,0.0006416751],"domain_scores_gemma":[0.9989096,0.0001739248,0.0001054526,0.0005248257,0.0001024325,0.0001837615],"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":[0.00001073165,0.00002514161,0.000005670428,0.00009363272,0.000009436414,0.000004565978,0.0001906452,0.02615741,0.9720367,0.00009433155,0.0001989547,0.001172782],"study_design_scores_gemma":[0.0006727073,0.00003408083,0.001931412,0.00005912967,0.0000141012,0.00002116088,0.00008622276,0.003165673,0.9926056,0.00008507684,0.0008870558,0.0004377794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925477,0.00008187944,0.00253969,0.0001291707,0.002224859,0.0007258161,0.00005800249,0.0009618581,0.0007310287],"genre_scores_gemma":[0.9764006,0.00001746647,0.02226079,0.0001739279,0.0002140671,0.0004939333,0.00003978455,0.00008485893,0.0003146112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02299174,"threshold_uncertainty_score":0.9999064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008088189985672399,"score_gpt":0.2063527970812832,"score_spread":0.1982646070956108,"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."}}